The Role of Perceptual Load in Object Recognition

Science.gov (United States)

Lavie, Nilli; Lin, Zhicheng; Zokaei, Nahid; Thoma, Volker

2009-01-01

Predictions from perceptual load theory (Lavie, 1995, 2005) regarding object recognition across the same or different viewpoints were tested. Results showed that high perceptual load reduces distracter recognition levels despite always presenting distracter objects from the same view. They also showed that the levels of distracter recognition were…

Fast neuromimetic object recognition using FPGA outperforms GPU implementations.

Science.gov (United States)

Orchard, Garrick; Martin, Jacob G; Vogelstein, R Jacob; Etienne-Cummings, Ralph

2013-08-01

Recognition of objects in still images has traditionally been regarded as a difficult computational problem. Although modern automated methods for visual object recognition have achieved steadily increasing recognition accuracy, even the most advanced computational vision approaches are unable to obtain performance equal to that of humans. This has led to the creation of many biologically inspired models of visual object recognition, among them the hierarchical model and X (HMAX) model. HMAX is traditionally known to achieve high accuracy in visual object recognition tasks at the expense of significant computational complexity. Increasing complexity, in turn, increases computation time, reducing the number of images that can be processed per unit time. In this paper we describe how the computationally intensive and biologically inspired HMAX model for visual object recognition can be modified for implementation on a commercial field-programmable aate Array, specifically the Xilinx Virtex 6 ML605 evaluation board with XC6VLX240T FPGA. We show that with minor modifications to the traditional HMAX model we can perform recognition on images of size 128 × 128 pixels at a rate of 190 images per second with a less than 1% loss in recognition accuracy in both binary and multiclass visual object recognition tasks.

Visual recognition and tracking of objects for robot sensing

International Nuclear Information System (INIS)

Lowe, D.G.

1994-01-01

An overview is presented of a number of techniques used for recognition and motion tracking of articulated 3-D objects. With recent advances in robust methods for model-based vision and improved performance of computer systems, it will soon be possible to build low-cost, high-reliability systems for model-based motion tracking. Such systems can be expected to open up a wide range of applications in robotics by providing machines with real-time information about their environment. This paper describes a number of techniques for efficiently matching parameterized 3-D models to image features. The matching methods are robust with respect to missing and ambiguous features as well as measurement errors. Unlike most previous work on model-based motion tracking, this system provides for the integrated treatment of matching and measurement errors during motion tracking. The initial application is in a system for real-time motion tracking of articulated 3-D objects. With the future addition of an indexing component, these same techniques can also be used for general model-based recognition. The current real-time implementation is based on matching straight line segments, but some preliminary experiments on matching arbitrary curves are also described. (author)

Object Recognition and Localization: The Role of Tactile Sensors

Directory of Open Access Journals (Sweden)

Achint Aggarwal

2014-02-01

Full Text Available Tactile sensors, because of their intrinsic insensitivity to lighting conditions and water turbidity, provide promising opportunities for augmenting the capabilities of vision sensors in applications involving object recognition and localization. This paper presents two approaches for haptic object recognition and localization for ground and underwater environments. The first approach called Batch Ransac and Iterative Closest Point augmented Particle Filter (BRICPPF is based on an innovative combination of particle filters, Iterative-Closest-Point algorithm, and a feature-based Random Sampling and Consensus (RANSAC algorithm for database matching. It can handle a large database of 3D-objects of complex shapes and performs a complete six-degree-of-freedom localization of static objects. The algorithms are validated by experimentation in ground and underwater environments using real hardware. To our knowledge this is the first instance of haptic object recognition and localization in underwater environments. The second approach is biologically inspired, and provides a close integration between exploration and recognition. An edge following exploration strategy is developed that receives feedback from the current state of recognition. A recognition by parts approach is developed which uses the BRICPPF for object sub-part recognition. Object exploration is either directed to explore a part until it is successfully recognized, or is directed towards new parts to endorse the current recognition belief. This approach is validated by simulation experiments.

Object recognition memory: neurobiological mechanisms of encoding, consolidation and retrieval.

Science.gov (United States)

Winters, Boyer D; Saksida, Lisa M; Bussey, Timothy J

2008-07-01

Tests of object recognition memory, or the judgment of the prior occurrence of an object, have made substantial contributions to our understanding of the nature and neurobiological underpinnings of mammalian memory. Only in recent years, however, have researchers begun to elucidate the specific brain areas and neural processes involved in object recognition memory. The present review considers some of this recent research, with an emphasis on studies addressing the neural bases of perirhinal cortex-dependent object recognition memory processes. We first briefly discuss operational definitions of object recognition and the common behavioural tests used to measure it in non-human primates and rodents. We then consider research from the non-human primate and rat literature examining the anatomical basis of object recognition memory in the delayed nonmatching-to-sample (DNMS) and spontaneous object recognition (SOR) tasks, respectively. The results of these studies overwhelmingly favor the view that perirhinal cortex (PRh) is a critical region for object recognition memory. We then discuss the involvement of PRh in the different stages--encoding, consolidation, and retrieval--of object recognition memory. Specifically, recent work in rats has indicated that neural activity in PRh contributes to object memory encoding, consolidation, and retrieval processes. Finally, we consider the pharmacological, cellular, and molecular factors that might play a part in PRh-mediated object recognition memory. Recent studies in rodents have begun to indicate the remarkable complexity of the neural substrates underlying this seemingly simple aspect of declarative memory.

Color descriptors for object category recognition

NARCIS (Netherlands)

van de Sande, K.E.A.; Gevers, T.; Snoek, C.G.M.

2008-01-01

Category recognition is important to access visual information on the level of objects. A common approach is to compute image descriptors first and then to apply machine learning to achieve category recognition from annotated examples. As a consequence, the choice of image descriptors is of great

Use of the recognition heuristic depends on the domain's recognition validity, not on the recognition validity of selected sets of objects.

Science.gov (United States)

Pohl, Rüdiger F; Michalkiewicz, Martha; Erdfelder, Edgar; Hilbig, Benjamin E

2017-07-01

According to the recognition-heuristic theory, decision makers solve paired comparisons in which one object is recognized and the other not by recognition alone, inferring that recognized objects have higher criterion values than unrecognized ones. However, success-and thus usefulness-of this heuristic depends on the validity of recognition as a cue, and adaptive decision making, in turn, requires that decision makers are sensitive to it. To this end, decision makers could base their evaluation of the recognition validity either on the selected set of objects (the set's recognition validity), or on the underlying domain from which the objects were drawn (the domain's recognition validity). In two experiments, we manipulated the recognition validity both in the selected set of objects and between domains from which the sets were drawn. The results clearly show that use of the recognition heuristic depends on the domain's recognition validity, not on the set's recognition validity. In other words, participants treat all sets as roughly representative of the underlying domain and adjust their decision strategy adaptively (only) with respect to the more general environment rather than the specific items they are faced with.

Very deep recurrent convolutional neural network for object recognition

Science.gov (United States)

Brahimi, Sourour; Ben Aoun, Najib; Ben Amar, Chokri

2017-03-01

In recent years, Computer vision has become a very active field. This field includes methods for processing, analyzing, and understanding images. The most challenging problems in computer vision are image classification and object recognition. This paper presents a new approach for object recognition task. This approach exploits the success of the Very Deep Convolutional Neural Network for object recognition. In fact, it improves the convolutional layers by adding recurrent connections. This proposed approach was evaluated on two object recognition benchmarks: Pascal VOC 2007 and CIFAR-10. The experimental results prove the efficiency of our method in comparison with the state of the art methods.

Object recognition in images by human vision and computer vision

NARCIS (Netherlands)

Chen, Q.; Dijkstra, J.; Vries, de B.

2010-01-01

Object recognition plays a major role in human behaviour research in the built environment. Computer based object recognition techniques using images as input are challenging, but not an adequate representation of human vision. This paper reports on the differences in object shape recognition

Representing Objects using Global 3D Relational Features for Recognition Tasks

DEFF Research Database (Denmark)

Mustafa, Wail

2015-01-01

representations. For representing objects, we derive global descriptors encoding shape using viewpoint-invariant features obtained from multiple sensors observing the scene. Objects are also described using color independently. This allows for combining color and shape when it is required for the task. For more...... robust color description, color calibration is performed. The framework was used in three recognition tasks: object instance recognition, object category recognition, and object spatial relationship recognition. For the object instance recognition task, we present a system that utilizes color and scale...

Geometric Edge Description and Classification in Point Cloud Data with Application to 3D Object Recognition

DEFF Research Database (Denmark)

Jørgensen, Troels Bo; Buch, Anders Glent; Kraft, Dirk

2015-01-01

descriptor allows for both fast computation and fast processing by having a low dimension, while still producing highly reliable edge detections. Lastly, we use our features in a 3D object recognition application using a well-established benchmark. We show that our edge features allow for significant...

Running Improves Pattern Separation during Novel Object Recognition.

Science.gov (United States)

Bolz, Leoni; Heigele, Stefanie; Bischofberger, Josef

2015-10-09

Running increases adult neurogenesis and improves pattern separation in various memory tasks including context fear conditioning or touch-screen based spatial learning. However, it is unknown whether pattern separation is improved in spontaneous behavior, not emotionally biased by positive or negative reinforcement. Here we investigated the effect of voluntary running on pattern separation during novel object recognition in mice using relatively similar or substantially different objects.We show that running increases hippocampal neurogenesis but does not affect object recognition memory with 1.5 h delay after sample phase. By contrast, at 24 h delay, running significantly improves recognition memory for similar objects, whereas highly different objects can be distinguished by both, running and sedentary mice. These data show that physical exercise improves pattern separation, independent of negative or positive reinforcement. In sedentary mice there is a pronounced temporal gradient for remembering object details. In running mice, however, increased neurogenesis improves hippocampal coding and temporally preserves distinction of novel objects from familiar ones.

Utilization-based object recognition in confined spaces

Science.gov (United States)

Shirkhodaie, Amir; Telagamsetti, Durga; Chan, Alex L.

2017-05-01

Recognizing substantially occluded objects in confined spaces is a very challenging problem for ground-based persistent surveillance systems. In this paper, we discuss the ontology inference of occluded object recognition in the context of in-vehicle group activities (IVGA) and describe an approach that we refer to as utilization-based object recognition method. We examine the performance of three types of classifiers tailored for the recognition of objects with partial visibility, namely, (1) Hausdorff Distance classifier, (2) Hamming Network classifier, and (3) Recurrent Neural Network classifier. In order to train these classifiers, we have generated multiple imagery datasets containing a mixture of common objects appearing inside a vehicle with full or partial visibility and occultation. To generate dynamic interactions between multiple people, we model the IVGA scenarios using a virtual simulation environment, in which a number of simulated actors perform a variety of IVGA tasks independently or jointly. This virtual simulation engine produces the much needed imagery datasets for the verification and validation of the efficiency and effectiveness of the selected object recognizers. Finally, we improve the performance of these object recognizers by incorporating human gestural information that differentiates various object utilization or handling methods through the analyses of dynamic human-object interactions (HOI), human-human interactions (HHI), and human-vehicle interactions (HVI) in the context of IVGA.

Object recognition with hierarchical discriminant saliency networks.

Science.gov (United States)

Han, Sunhyoung; Vasconcelos, Nuno

2014-01-01

The benefits of integrating attention and object recognition are investigated. While attention is frequently modeled as a pre-processor for recognition, we investigate the hypothesis that attention is an intrinsic component of recognition and vice-versa. This hypothesis is tested with a recognition model, the hierarchical discriminant saliency network (HDSN), whose layers are top-down saliency detectors, tuned for a visual class according to the principles of discriminant saliency. As a model of neural computation, the HDSN has two possible implementations. In a biologically plausible implementation, all layers comply with the standard neurophysiological model of visual cortex, with sub-layers of simple and complex units that implement a combination of filtering, divisive normalization, pooling, and non-linearities. In a convolutional neural network implementation, all layers are convolutional and implement a combination of filtering, rectification, and pooling. The rectification is performed with a parametric extension of the now popular rectified linear units (ReLUs), whose parameters can be tuned for the detection of target object classes. This enables a number of functional enhancements over neural network models that lack a connection to saliency, including optimal feature denoising mechanisms for recognition, modulation of saliency responses by the discriminant power of the underlying features, and the ability to detect both feature presence and absence. In either implementation, each layer has a precise statistical interpretation, and all parameters are tuned by statistical learning. Each saliency detection layer learns more discriminant saliency templates than its predecessors and higher layers have larger pooling fields. This enables the HDSN to simultaneously achieve high selectivity to target object classes and invariance. The performance of the network in saliency and object recognition tasks is compared to those of models from the biological and

Model-based recognition of 3-D objects by geometric hashing technique

International Nuclear Information System (INIS)

Severcan, M.; Uzunalioglu, H.

1992-09-01

A model-based object recognition system is developed for recognition of polyhedral objects. The system consists of feature extraction, modelling and matching stages. Linear features are used for object descriptions. Lines are obtained from edges using rotation transform. For modelling and recognition process, geometric hashing method is utilized. Each object is modelled using 2-D views taken from the viewpoints on the viewing sphere. A hidden line elimination algorithm is used to find these views from the wire frame model of the objects. The recognition experiments yielded satisfactory results. (author). 8 refs, 5 figs

Experience moderates overlap between object and face recognition, suggesting a common ability.

Science.gov (United States)

Gauthier, Isabel; McGugin, Rankin W; Richler, Jennifer J; Herzmann, Grit; Speegle, Magen; Van Gulick, Ana E

2014-07-03

Some research finds that face recognition is largely independent from the recognition of other objects; a specialized and innate ability to recognize faces could therefore have little or nothing to do with our ability to recognize objects. We propose a new framework in which recognition performance for any category is the product of domain-general ability and category-specific experience. In Experiment 1, we show that the overlap between face and object recognition depends on experience with objects. In 256 subjects we measured face recognition, object recognition for eight categories, and self-reported experience with these categories. Experience predicted neither face recognition nor object recognition but moderated their relationship: Face recognition performance is increasingly similar to object recognition performance with increasing object experience. If a subject has a lot of experience with objects and is found to perform poorly, they also prove to have a low ability with faces. In a follow-up survey, we explored the dimensions of experience with objects that may have contributed to self-reported experience in Experiment 1. Different dimensions of experience appear to be more salient for different categories, with general self-reports of expertise reflecting judgments of verbal knowledge about a category more than judgments of visual performance. The complexity of experience and current limitations in its measurement support the importance of aggregating across multiple categories. Our findings imply that both face and object recognition are supported by a common, domain-general ability expressed through experience with a category and best measured when accounting for experience. © 2014 ARVO.

Reliable Gait Recognition Using 3D Reconstructions and Random Forests - An Anthropometric Approach

DEFF Research Database (Denmark)

Sandau, Martin; Heimbürger, Rikke V.; Jensen, Karl E.

2016-01-01

reliable recognition. Sixteen participants performed normal walking where 3D reconstructions were obtained continually. Segment lengths and kinematics from the extremities were manually extracted by eight expert observers. The results showed that all the participants were recognized, assuming the same...... expert annotated the data. Recognition based on data annotated by different experts was less reliable achieving 72.6% correct recognitions as some parameters were heavily affected by interobserver variability. This study verified that 3D reconstructions are feasible for forensic gait analysis...

Object Recognition Memory and the Rodent Hippocampus

Science.gov (United States)

Broadbent, Nicola J.; Gaskin, Stephane; Squire, Larry R.; Clark, Robert E.

2010-01-01

In rodents, the novel object recognition task (NOR) has become a benchmark task for assessing recognition memory. Yet, despite its widespread use, a consensus has not developed about which brain structures are important for task performance. We assessed both the anterograde and retrograde effects of hippocampal lesions on performance in the NOR…

Sensor agnostic object recognition using a map seeking circuit

Science.gov (United States)

Overman, Timothy L.; Hart, Michael

2012-05-01

Automatic object recognition capabilities are traditionally tuned to exploit the specific sensing modality they were designed to. Their successes (and shortcomings) are tied to object segmentation from the background, they typically require highly skilled personnel to train them, and they become cumbersome with the introduction of new objects. In this paper we describe a sensor independent algorithm based on the biologically inspired technology of map seeking circuits (MSC) which overcomes many of these obstacles. In particular, the MSC concept offers transparency in object recognition from a common interface to all sensor types, analogous to a USB device. It also provides a common core framework that is independent of the sensor and expandable to support high dimensionality decision spaces. Ease in training is assured by using commercially available 3D models from the video game community. The search time remains linear no matter how many objects are introduced, ensuring rapid object recognition. Here, we report results of an MSC algorithm applied to object recognition and pose estimation from high range resolution radar (1D), electrooptical imagery (2D), and LIDAR point clouds (3D) separately. By abstracting the sensor phenomenology from the underlying a prior knowledge base, MSC shows promise as an easily adaptable tool for incorporating additional sensor inputs.

Real object recognition using moment invariants

Indian Academy of Sciences (India)

are taken from different angles of view are the main features leading us to our objective. ... Two-dimensional moments of a digitally sampled M × M image that has gray function f (x, y), (x, .... in this paper. Information about the original colours of the objects is not used. .... multi-dimensional changes and recognition. Table 1.

Possibility of object recognition using Altera's model based design approach

International Nuclear Information System (INIS)

Tickle, A J; Harvey, P K; Smith, J S; Wu, F

2009-01-01

Object recognition is an image processing task of finding a given object in a selected image or video sequence. Object recognition can be divided into two areas: one of these is decision-theoretic and deals with patterns described by quantitative descriptors, for example such as length, area, shape and texture. With this Graphical User Interface Circuitry (GUIC) methodology employed here being relatively new for object recognition systems, the aim of this work is to identify if the developed circuitry can detect certain shapes or strings within the target image. A much smaller reference image feeds the preset data for identification, tests are conducted for both binary and greyscale and the additional mathematical morphology to highlight the area within the target image with the object(s) are located is also presented. This then provides proof that basic recognition methods are valid and would allow the progression to developing decision-theoretical and learning based approaches using GUICs for use in multidisciplinary tasks.

Three-dimensional object recognition using similar triangles and decision trees

Science.gov (United States)

Spirkovska, Lilly

1993-01-01

A system, TRIDEC, that is capable of distinguishing between a set of objects despite changes in the objects' positions in the input field, their size, or their rotational orientation in 3D space is described. TRIDEC combines very simple yet effective features with the classification capabilities of inductive decision tree methods. The feature vector is a list of all similar triangles defined by connecting all combinations of three pixels in a coarse coded 127 x 127 pixel input field. The classification is accomplished by building a decision tree using the information provided from a limited number of translated, scaled, and rotated samples. Simulation results are presented which show that TRIDEC achieves 94 percent recognition accuracy in the 2D invariant object recognition domain and 98 percent recognition accuracy in the 3D invariant object recognition domain after training on only a small sample of transformed views of the objects.

An ERP Study on Self-Relevant Object Recognition

Science.gov (United States)

Miyakoshi, Makoto; Nomura, Michio; Ohira, Hideki

2007-01-01

We performed an event-related potential study to investigate the self-relevance effect in object recognition. Three stimulus categories were prepared: SELF (participant's own objects), FAMILIAR (disposable and public objects, defined as objects with less-self-relevant familiarity), and UNFAMILIAR (others' objects). The participants' task was to…

On the relation between face and object recognition in developmental prosopagnosia

DEFF Research Database (Denmark)

Gerlach, Christian; Klargaard, Solja K.; Starrfelt, Randi

2016-01-01

There is an ongoing debate about whether face recognition and object recognition constitute separate domains. Clarification of this issue can have important theoretical implications as face recognition is often used as a prime example of domain-specificity in mind and brain. An important source...... of input to this debate comes from studies of individuals with developmental prosopagnosia, suggesting that face recognition can be selectively impaired. We put the selectivity hypothesis to test by assessing the performance of 10 individuals with developmental prosopagnosia on demanding tests of visual...... object processing involving both regular and degraded drawings. None of the individuals exhibited a clear dissociation between face and object recognition, and as a group they were significantly more affected by degradation of objects than control participants. Importantly, we also find positive...

Exploring objects for recognition in the real world

NARCIS (Netherlands)

Kootstra, Gert; Ypma, Jelmer; de Boer, Bart

2007-01-01

Perception in natural systems is a highly active process. In this paper, we adopt the strategy of natural systems to explore objects for 3D object recognition using robots. The exploration of objects enables the system to learn objects from different viewpoints, which is essential for 3D object

Object recognition - Convergence of vision, audition, and touch

DEFF Research Database (Denmark)

Kassuba, Tanja

of object information across audition and touch or across all thee senses. Further, even though object recognition within different senses is to some degree redundant, the different senses differ with respect to their intrinsic efficiency in extracting types of information (Lederman & Klatzky, 2009...... magnetic resonance imaging (fMRI), diffusion tensor imaging (DTI), and repetitive transcranial magnetic stimulation (rTMS). The following research questions were addressed: 1. Where in the human brain does object recognition converge across vision, audition, and touch? 2. How is audio-haptic object......-match-to-sample task was applied in which participants had to match a target object with a previously presented sample object within and across audition and touch in both directions (auditory─haptic and haptic─auditory). As a coherence in content is an important binding cue (Laurienti et al., 2004), semantic...

Comparison of Object Recognition Behavior in Human and Monkey

Science.gov (United States)

Rajalingham, Rishi; Schmidt, Kailyn

2015-01-01

Although the rhesus monkey is used widely as an animal model of human visual processing, it is not known whether invariant visual object recognition behavior is quantitatively comparable across monkeys and humans. To address this question, we systematically compared the core object recognition behavior of two monkeys with that of human subjects. To test true object recognition behavior (rather than image matching), we generated several thousand naturalistic synthetic images of 24 basic-level objects with high variation in viewing parameters and image background. Monkeys were trained to perform binary object recognition tasks on a match-to-sample paradigm. Data from 605 human subjects performing the same tasks on Mechanical Turk were aggregated to characterize “pooled human” object recognition behavior, as well as 33 separate Mechanical Turk subjects to characterize individual human subject behavior. Our results show that monkeys learn each new object in a few days, after which they not only match mean human performance but show a pattern of object confusion that is highly correlated with pooled human confusion patterns and is statistically indistinguishable from individual human subjects. Importantly, this shared human and monkey pattern of 3D object confusion is not shared with low-level visual representations (pixels, V1+; models of the retina and primary visual cortex) but is shared with a state-of-the-art computer vision feature representation. Together, these results are consistent with the hypothesis that rhesus monkeys and humans share a common neural shape representation that directly supports object perception. SIGNIFICANCE STATEMENT To date, several mammalian species have shown promise as animal models for studying the neural mechanisms underlying high-level visual processing in humans. In light of this diversity, making tight comparisons between nonhuman and human primates is particularly critical in determining the best use of nonhuman primates to

PROBABILISTIC APPROACH TO OBJECT DETECTION AND RECOGNITION FOR VIDEOSTREAM PROCESSING

Directory of Open Access Journals (Sweden)

Volodymyr Kharchenko

2017-07-01

Full Text Available Purpose: The represented research results are aimed to improve theoretical basics of computer vision and artificial intelligence of dynamical system. Proposed approach of object detection and recognition is based on probabilistic fundamentals to ensure the required level of correct object recognition. Methods: Presented approach is grounded at probabilistic methods, statistical methods of probability density estimation and computer-based simulation at verification stage of development. Results: Proposed approach for object detection and recognition for video stream data processing has shown several advantages in comparison with existing methods due to its simple realization and small time of data processing. Presented results of experimental verification look plausible for object detection and recognition in video stream. Discussion: The approach can be implemented in dynamical system within changeable environment such as remotely piloted aircraft systems and can be a part of artificial intelligence in navigation and control systems.

Perceptual Plasticity for Auditory Object Recognition

Science.gov (United States)

Heald, Shannon L. M.; Van Hedger, Stephen C.; Nusbaum, Howard C.

2017-01-01

In our auditory environment, we rarely experience the exact acoustic waveform twice. This is especially true for communicative signals that have meaning for listeners. In speech and music, the acoustic signal changes as a function of the talker (or instrument), speaking (or playing) rate, and room acoustics, to name a few factors. Yet, despite this acoustic variability, we are able to recognize a sentence or melody as the same across various kinds of acoustic inputs and determine meaning based on listening goals, expectations, context, and experience. The recognition process relates acoustic signals to prior experience despite variability in signal-relevant and signal-irrelevant acoustic properties, some of which could be considered as “noise” in service of a recognition goal. However, some acoustic variability, if systematic, is lawful and can be exploited by listeners to aid in recognition. Perceivable changes in systematic variability can herald a need for listeners to reorganize perception and reorient their attention to more immediately signal-relevant cues. This view is not incorporated currently in many extant theories of auditory perception, which traditionally reduce psychological or neural representations of perceptual objects and the processes that act on them to static entities. While this reduction is likely done for the sake of empirical tractability, such a reduction may seriously distort the perceptual process to be modeled. We argue that perceptual representations, as well as the processes underlying perception, are dynamically determined by an interaction between the uncertainty of the auditory signal and constraints of context. This suggests that the process of auditory recognition is highly context-dependent in that the identity of a given auditory object may be intrinsically tied to its preceding context. To argue for the flexible neural and psychological updating of sound-to-meaning mappings across speech and music, we draw upon examples

Design and recognition of artificial landmarks for reliable indoor self-localization of mobile robots

Directory of Open Access Journals (Sweden)

Xu Zhong

2017-02-01

Full Text Available This article presents a self-localization scheme for indoor mobile robot navigation based on reliable design and recognition of artificial visual landmarks. Each landmark is patterned with a set of concentric circular rings in black and white, which reliably encodes the landmark’s identity under environmental illumination. A mobile robot in navigation uses an onboard camera to capture landmarks in the environment. The landmarks in an image are detected and identified using a bilayer recognition algorithm: A global recognition process initially extracts candidate landmark regions across the whole image and tries to identify enough landmarks; if necessary, a local recognition process locally enhances those unidentified regions of interest influenced by illumination and incompleteness and reidentifies them. The recognized landmarks are used to estimate the position and orientation of the onboard camera in the environment, based on the geometric relationship between the image and environmental frames. The experiments carried out in a real indoor environment show high robustness of the proposed landmark design and recognition scheme to the illumination condition, which leads to reliable and accurate mobile robot localization.

Exploiting core knowledge for visual object recognition.

Science.gov (United States)

Schurgin, Mark W; Flombaum, Jonathan I

2017-03-01

Humans recognize thousands of objects, and with relative tolerance to variable retinal inputs. The acquisition of this ability is not fully understood, and it remains an area in which artificial systems have yet to surpass people. We sought to investigate the memory process that supports object recognition. Specifically, we investigated the association of inputs that co-occur over short periods of time. We tested the hypothesis that human perception exploits expectations about object kinematics to limit the scope of association to inputs that are likely to have the same token as a source. In several experiments we exposed participants to images of objects, and we then tested recognition sensitivity. Using motion, we manipulated whether successive encounters with an image took place through kinematics that implied the same or a different token as the source of those encounters. Images were injected with noise, or shown at varying orientations, and we included 2 manipulations of motion kinematics. Across all experiments, memory performance was better for images that had been previously encountered with kinematics that implied a single token. A model-based analysis similarly showed greater memory strength when images were shown via kinematics that implied a single token. These results suggest that constraints from physics are built into the mechanisms that support memory about objects. Such constraints-often characterized as 'Core Knowledge'-are known to support perception and cognition broadly, even in young infants. But they have never been considered as a mechanism for memory with respect to recognition. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Training facilitates object recognition in cubist paintings

Directory of Open Access Journals (Sweden)

Martin Wiesmann

2010-03-01

Full Text Available To the naïve observer, cubist paintings contain geometrical forms in which familiar objects are hardly recognizable, even in the presence of a meaningful title. We used fMRI to test whether a short training session about Cubism would facilitate object recognition in paintings by Picasso, Braque and Gris. Subjects, who had no formal art education, were presented with titled or untitled cubist paintings and scrambled images, and performed object recognition tasks. Relative to the control group, trained subjects recognized more objects in the paintings, their response latencies were significantly shorter, and they showed enhanced activation in the parahippocampal cortex, with a parametric increase in the amplitude of the fMRI signal as a function of the number of recognized objects. Moreover, trained subjects were slower to report not recognizing any familiar objects in the paintings and these longer response latencies were correlated with activation in a fronto-parietal network. These findings suggest that trained subjects adopted a visual search strategy and used contextual associations to perform the tasks. Our study supports the proactive brain framework, according to which the brain uses associations to generate predictions.

It takes two-skilled recognition of objects engages lateral areas in both hemispheres.

Directory of Open Access Journals (Sweden)

Merim Bilalić

Full Text Available Our object recognition abilities, a direct product of our experience with objects, are fine-tuned to perfection. Left temporal and lateral areas along the dorsal, action related stream, as well as left infero-temporal areas along the ventral, object related stream are engaged in object recognition. Here we show that expertise modulates the activity of dorsal areas in the recognition of man-made objects with clearly specified functions. Expert chess players were faster than chess novices in identifying chess objects and their functional relations. Experts' advantage was domain-specific as there were no differences between groups in a control task featuring geometrical shapes. The pattern of eye movements supported the notion that experts' extensive knowledge about domain objects and their functions enabled superior recognition even when experts were not directly fixating the objects of interest. Functional magnetic resonance imaging (fMRI related exclusively the areas along the dorsal stream to chess specific object recognition. Besides the commonly involved left temporal and parietal lateral brain areas, we found that only in experts homologous areas on the right hemisphere were also engaged in chess specific object recognition. Based on these results, we discuss whether skilled object recognition does not only involve a more efficient version of the processes found in non-skilled recognition, but also qualitatively different cognitive processes which engage additional brain areas.

Higher-Order Neural Networks Applied to 2D and 3D Object Recognition

Science.gov (United States)

Spirkovska, Lilly; Reid, Max B.

1994-01-01

A Higher-Order Neural Network (HONN) can be designed to be invariant to geometric transformations such as scale, translation, and in-plane rotation. Invariances are built directly into the architecture of a HONN and do not need to be learned. Thus, for 2D object recognition, the network needs to be trained on just one view of each object class, not numerous scaled, translated, and rotated views. Because the 2D object recognition task is a component of the 3D object recognition task, built-in 2D invariance also decreases the size of the training set required for 3D object recognition. We present results for 2D object recognition both in simulation and within a robotic vision experiment and for 3D object recognition in simulation. We also compare our method to other approaches and show that HONNs have distinct advantages for position, scale, and rotation-invariant object recognition. The major drawback of HONNs is that the size of the input field is limited due to the memory required for the large number of interconnections in a fully connected network. We present partial connectivity strategies and a coarse-coding technique for overcoming this limitation and increasing the input field to that required by practical object recognition problems.

Perceptual differentiation and category effects in normal object recognition

DEFF Research Database (Denmark)

Gerlach, Christian; Law, I; Gade, A

1999-01-01

The purpose of the present PET study was (i) to investigate the neural correlates of object recognition, i.e. the matching of visual forms to memory, and (ii) to test the hypothesis that this process is more difficult for natural objects than for artefacts. This was done by using object decision...... tasks where subjects decided whether pictures represented real objects or non-objects. The object decision tasks differed in their difficulty (the degree of perceptual differentiation needed to perform them) and in the category of the real objects used (natural objects versus artefacts). A clear effect...... be the neural correlate of matching visual forms to memory, and the amount of activation in these regions may correspond to the degree of perceptual differentiation required for recognition to occur. With respect to behaviour, it took significantly longer to make object decisions on natural objects than...

A Patient with Difficulty of Object Recognition: Semantic Amnesia for Manipulable Objects

Directory of Open Access Journals (Sweden)

A. Yamadori

1992-01-01

Full Text Available We studied a patient who had recognition difficulty for manipulable objects. MRI showed a lesion in the left occipito-parietotemporal area. Differential diagnosis of agnosia, aphasia and apraxia is discussed. We believe this “object meaning amnesia” constitutes a distinct subtype of semantic amnesia.

Leveraging Cognitive Context for Object Recognition

Science.gov (United States)

2014-06-01

established, links have an associated strength value which affects how much activation is passed along the link from chunk j to chunk i. Link strengths ... strength is updated iteratively whenever the model thinks about chunks i context suggests that an apple is most likely to be seen next (since it primes...1998. 1, 4 [3] M. E. Auckland , K. R. Cave, and N. Donnelly. Non- target objects can influence perceptual processes dur- ing object recognition

An Innovative SIFT-Based Method for Rigid Video Object Recognition

Directory of Open Access Journals (Sweden)

Jie Yu

2014-01-01

Full Text Available This paper presents an innovative SIFT-based method for rigid video object recognition (hereafter called RVO-SIFT. Just like what happens in the vision system of human being, this method makes the object recognition and feature updating process organically unify together, using both trajectory and feature matching, and thereby it can learn new features not only in the training stage but also in the recognition stage, which can improve greatly the completeness of the video object’s features automatically and, in turn, increases the ratio of correct recognition drastically. The experimental results on real video sequences demonstrate its surprising robustness and efficiency.

Brain dynamics of upstream perceptual processes leading to visual object recognition: a high density ERP topographic mapping study.

Science.gov (United States)

Schettino, Antonio; Loeys, Tom; Delplanque, Sylvain; Pourtois, Gilles

2011-04-01

Recent studies suggest that visual object recognition is a proactive process through which perceptual evidence accumulates over time before a decision can be made about the object. However, the exact electrophysiological correlates and time-course of this complex process remain unclear. In addition, the potential influence of emotion on this process has not been investigated yet. We recorded high density EEG in healthy adult participants performing a novel perceptual recognition task. For each trial, an initial blurred visual scene was first shown, before the actual content of the stimulus was gradually revealed by progressively adding diagnostic high spatial frequency information. Participants were asked to stop this stimulus sequence as soon as they could correctly perform an animacy judgment task. Behavioral results showed that participants reliably gathered perceptual evidence before recognition. Furthermore, prolonged exploration times were observed for pleasant, relative to either neutral or unpleasant scenes. ERP results showed distinct effects starting at 280 ms post-stimulus onset in distant brain regions during stimulus processing, mainly characterized by: (i) a monotonic accumulation of evidence, involving regions of the posterior cingulate cortex/parahippocampal gyrus, and (ii) true categorical recognition effects in medial frontal regions, including the dorsal anterior cingulate cortex. These findings provide evidence for the early involvement, following stimulus onset, of non-overlapping brain networks during proactive processes eventually leading to visual object recognition. Copyright © 2011 Elsevier Inc. All rights reserved.

What are the visual features underlying rapid object recognition?

Directory of Open Access Journals (Sweden)

Sébastien M Crouzet

2011-11-01

Full Text Available Research progress in machine vision has been very significant in recent years. Robust face detection and identification algorithms are already readily available to consumers, and modern computer vision algorithms for generic object recognition are now coping with the richness and complexity of natural visual scenes. Unlike early vision models of object recognition that emphasized the role of figure-ground segmentation and spatial information between parts, recent successful approaches are based on the computation of loose collections of image features without prior segmentation or any explicit encoding of spatial relations. While these models remain simplistic models of visual processing, they suggest that, in principle, bottom-up activation of a loose collection of image features could support the rapid recognition of natural object categories and provide an initial coarse visual representation before more complex visual routines and attentional mechanisms take place. Focusing on biologically-plausible computational models of (bottom-up pre-attentive visual recognition, we review some of the key visual features that have been described in the literature. We discuss the consistency of these feature-based representations with classical theories from visual psychology and test their ability to account for human performance on a rapid object categorization task.

Differential effects of spaced vs. massed training in long-term object-identity and object-location recognition memory.

Science.gov (United States)

Bello-Medina, Paola C; Sánchez-Carrasco, Livia; González-Ornelas, Nadia R; Jeffery, Kathryn J; Ramírez-Amaya, Víctor

2013-08-01

Here we tested whether the well-known superiority of spaced training over massed training is equally evident in both object identity and object location recognition memory. We trained animals with objects placed in a variable or in a fixed location to produce a location-independent object identity memory or a location-dependent object representation. The training consisted of 5 trials that occurred either on one day (Massed) or over the course of 5 consecutive days (Spaced). The memory test was done in independent groups of animals either 24h or 7 days after the last training trial. In each test the animals were exposed to either a novel object, when trained with the objects in variable locations, or to a familiar object in a novel location, when trained with objects in fixed locations. The difference in time spent exploring the changed versus the familiar objects was used as a measure of recognition memory. For the object-identity-trained animals, spaced training produced clear evidence of recognition memory after both 24h and 7 days, but massed-training animals showed it only after 24h. In contrast, for the object-location-trained animals, recognition memory was evident after both retention intervals and with both training procedures. When objects were placed in variable locations for the two types of training and the test was done with a brand-new location, only the spaced-training animals showed recognition at 24h, but surprisingly, after 7 days, animals trained using both procedures were able to recognize the change, suggesting a post-training consolidation process. We suggest that the two training procedures trigger different neural mechanisms that may differ in the two segregated streams that process object information and that may consolidate differently. Copyright © 2013 Elsevier B.V. All rights reserved.

Object and event recognition for stroke rehabilitation

Science.gov (United States)

Ghali, Ahmed; Cunningham, Andrew S.; Pridmore, Tony P.

2003-06-01

Stroke is a major cause of disability and health care expenditure around the world. Existing stroke rehabilitation methods can be effective but are costly and need to be improved. Even modest improvements in the effectiveness of rehabilitation techniques could produce large benefits in terms of quality of life. The work reported here is part of an ongoing effort to integrate virtual reality and machine vision technologies to produce innovative stroke rehabilitation methods. We describe a combined object recognition and event detection system that provides real time feedback to stroke patients performing everyday kitchen tasks necessary for independent living, e.g. making a cup of coffee. The image plane position of each object, including the patient"s hand, is monitored using histogram-based recognition methods. The relative positions of hand and objects are then reported to a task monitor that compares the patient"s actions against a model of the target task. A prototype system has been constructed and is currently undergoing technical and clinical evaluation.

The role of nitric oxide in the object recognition memory.

Science.gov (United States)

Pitsikas, Nikolaos

2015-05-15

The novel object recognition task (NORT) assesses recognition memory in animals. It is a non-rewarded paradigm that it is based on spontaneous exploratory behavior in rodents. This procedure is widely used for testing the effects of compounds on recognition memory. Recognition memory is a type of memory severely compromised in schizophrenic and Alzheimer's disease patients. Nitric oxide (NO) is sought to be an intra- and inter-cellular messenger in the central nervous system and its implication in learning and memory is well documented. Here I intended to critically review the role of NO-related compounds on different aspects of recognition memory. Current analysis shows that both NO donors and NO synthase (NOS) inhibitors are involved in object recognition memory and suggests that NO might be a promising target for cognition impairments. However, the potential neurotoxicity of NO would add a note of caution in this context. Copyright © 2014 Elsevier B.V. All rights reserved.

Crossmodal object recognition in rats with and without multimodal object pre-exposure: no effect of hippocampal lesions.

Science.gov (United States)

Reid, James M; Jacklin, Derek L; Winters, Boyer D

2012-10-01

The neural mechanisms and brain circuitry involved in the formation, storage, and utilization of multisensory object representations are poorly understood. We have recently introduced a crossmodal object recognition (CMOR) task that enables the study of such questions in rats. Our previous research has indicated that the perirhinal and posterior parietal cortices functionally interact to mediate spontaneous (tactile-to-visual) CMOR performance in rats; however, it remains to be seen whether other brain regions, particularly those receiving polymodal sensory inputs, contribute to this cognitive function. In the current study, we assessed the potential contribution of one such polymodal region, the hippocampus (HPC), to crossmodal object recognition memory. Rats with bilateral excitotoxic HPC lesions were tested in two versions of crossmodal object recognition: (1) the original CMOR task, which requires rats to compare between a stored tactile object representation and visually-presented objects to discriminate the novel and familiar stimuli; and (2) a novel 'multimodal pre-exposure' version of the CMOR task (PE/CMOR), in which simultaneous exploration of the tactile and visual sensory features of an object 24 h prior to the sample phase enhances CMOR performance across longer retention delays. Hippocampus-lesioned rats performed normally on both crossmodal object recognition tasks, but were impaired on a radial arm maze test of spatial memory, demonstrating the functional effectiveness of the lesions. These results strongly suggest that the HPC, despite its polymodal anatomical connections, is not critically involved in tactile-to-visual crossmodal object recognition memory. Copyright © 2012 Elsevier Inc. All rights reserved.

Single prolonged stress impairs social and object novelty recognition in rats.

Science.gov (United States)

Eagle, Andrew L; Fitzpatrick, Chris J; Perrine, Shane A

2013-11-01

Posttraumatic stress disorder (PTSD) results from exposure to a traumatic event and manifests as re-experiencing, arousal, avoidance, and negative cognition/mood symptoms. Avoidant symptoms, as well as the newly defined negative cognitions/mood, are a serious complication leading to diminished interest in once important or positive activities, such as social interaction; however, the basis of these symptoms remains poorly understood. PTSD patients also exhibit impaired object and social recognition, which may underlie the avoidance and symptoms of negative cognition, such as social estrangement or diminished interest in activities. Previous studies have demonstrated that single prolonged stress (SPS), models PTSD phenotypes, including impairments in learning and memory. Therefore, it was hypothesized that SPS would impair social and object recognition memory. Male Sprague Dawley rats were exposed to SPS then tested in the social choice test (SCT) or novel object recognition test (NOR). These tests measure recognition of novelty over familiarity, a natural preference of rodents. Results show that SPS impaired preference for both social and object novelty. In addition, SPS impairment in social recognition may be caused by impaired behavioral flexibility, or an inability to shift behavior during the SCT. These results demonstrate that traumatic stress can impair social and object recognition memory, which may underlie certain avoidant symptoms or negative cognition in PTSD and be related to impaired behavioral flexibility. Copyright © 2013 Elsevier B.V. All rights reserved.

Electrophysiological evidence for effects of color knowledge in object recognition.

Science.gov (United States)

Lu, Aitao; Xu, Guiping; Jin, Hua; Mo, Lei; Zhang, Jijia; Zhang, John X

2010-01-29

Knowledge about the typical colors associated with familiar everyday objects (i.e., strawberries are red) is well-known to be represented in the conceptual semantic system. Evidence that such knowledge may also play a role in early perceptual processes for object recognition is scant. In the present ERP study, participants viewed a list of object pictures and detected infrequent stimulus repetitions. Results show that shortly after stimulus onset, ERP components indexing early perceptual processes, including N1, P2, and N2, differentiated between objects in their appropriate or congruent color from these objects in an inappropriate or incongruent color. Such congruence effect also occurred in N3 associated with semantic processing of pictures but not in N4 for domain-general semantic processing. Our results demonstrate a clear effect of color knowledge in early object recognition stages and support the following proposal-color as a surface property is stored in a multiple-memory system where pre-semantic perceptual and semantic conceptual representations interact during object recognition. (c) 2009 Elsevier Ireland Ltd. All rights reserved.

Category-specificity in visual object recognition

DEFF Research Database (Denmark)

Gerlach, Christian

2009-01-01

Are all categories of objects recognized in the same manner visually? Evidence from neuropsychology suggests they are not: some brain damaged patients are more impaired in recognizing natural objects than artefacts whereas others show the opposite impairment. Category-effects have also been...... demonstrated in neurologically intact subjects, but the findings are contradictory and there is no agreement as to why category-effects arise. This article presents a Pre-semantic Account of Category Effects (PACE) in visual object recognition. PACE assumes two processing stages: shape configuration (the...... binding of shape elements into elaborate shape descriptions) and selection (among competing representations in visual long-term memory), which are held to be differentially affected by the structural similarity between objects. Drawing on evidence from clinical studies, experimental studies...

Experimental acquisition of long-range portraits of objects and their recognition

International Nuclear Information System (INIS)

Buryi, E V; Kosykh, A E

1998-01-01

An experimental investigation was made of recognition of the perspectives of model objects on the basis of the shape of the envelope of a scattered laser pulse. Stable recognition of various perspectives of an object was found to be possible even for high ratios of the probe pulse duration to the time of its propagation along the object surface. (laser applications and other topics in quantum electronics)

Superior voice recognition in a patient with acquired prosopagnosia and object agnosia.

Science.gov (United States)

Hoover, Adria E N; Démonet, Jean-François; Steeves, Jennifer K E

2010-11-01

Anecdotally, it has been reported that individuals with acquired prosopagnosia compensate for their inability to recognize faces by using other person identity cues such as hair, gait or the voice. Are they therefore superior at the use of non-face cues, specifically voices, to person identity? Here, we empirically measure person and object identity recognition in a patient with acquired prosopagnosia and object agnosia. We quantify person identity (face and voice) and object identity (car and horn) recognition for visual, auditory, and bimodal (visual and auditory) stimuli. The patient is unable to recognize faces or cars, consistent with his prosopagnosia and object agnosia, respectively. He is perfectly able to recognize people's voices and car horns and bimodal stimuli. These data show a reverse shift in the typical weighting of visual over auditory information for audiovisual stimuli in a compromised visual recognition system. Moreover, the patient shows selectively superior voice recognition compared to the controls revealing that two different stimulus domains, persons and objects, may not be equally affected by sensory adaptation effects. This also implies that person and object identity recognition are processed in separate pathways. These data demonstrate that an individual with acquired prosopagnosia and object agnosia can compensate for the visual impairment and become quite skilled at using spared aspects of sensory processing. In the case of acquired prosopagnosia it is advantageous to develop a superior use of voices for person identity recognition in everyday life. Copyright © 2010 Elsevier Ltd. All rights reserved.

Object recognition with hierarchical discriminant saliency networks

Directory of Open Access Journals (Sweden)

Sunhyoung eHan

2014-09-01

Full Text Available The benefits of integrating attention and object recognition are investigated. While attention is frequently modeled as pre-processor for recognition, we investigate the hypothesis that attention is an intrinsic component of recognition and vice-versa. This hypothesis is tested with a recognitionmodel, the hierarchical discriminant saliency network (HDSN, whose layers are top-down saliency detectors, tuned for a visual class according to the principles of discriminant saliency. The HDSN has two possible implementations. In a biologically plausible implementation, all layers comply with the standard neurophysiological model of visual cortex, with sub-layers of simple and complex units that implement a combination of filtering, divisive normalization, pooling, and non-linearities. In a neuralnetwork implementation, all layers are convolutional and implement acombination of filtering, rectification, and pooling. The rectificationis performed with a parametric extension of the now popular rectified linearunits (ReLUs, whose parameters can be tuned for the detection of targetobject classes. This enables a number of functional enhancementsover neural network models that lack a connection to saliency, including optimal feature denoising mechanisms for recognition, modulation ofsaliency responses by the discriminant power of the underlying features,and the ability to detect both feature presence and absence.In either implementation, each layer has a precise statistical interpretation, and all parameters are tuned by statistical learning. Each saliency detection layer learns more discriminant saliency templates than its predecessors and higher layers have larger pooling fields. This enables the HDSN to simultaneously achieve high selectivity totarget object classes and invariance. The resulting performance demonstrates benefits for all the functional enhancements of the HDSN.

On the relation between face and object recognition in developmental prosopagnosia

DEFF Research Database (Denmark)

Gerlach, Christian; Klargaard, Solja; Starrfelt, Randi

2016-01-01

There is an ongoing debate about whether face recognition and object recognition constitute separate cognitive domains. Clarification of this issue can have important theoretical consequences as face recognition is often used as a prime example of domain-specificity in mind and brain. An importan...

Central administration of angiotensin IV rapidly enhances novel object recognition among mice.

Science.gov (United States)

Paris, Jason J; Eans, Shainnel O; Mizrachi, Elisa; Reilley, Kate J; Ganno, Michelle L; McLaughlin, Jay P

2013-07-01

Angiotensin IV (Val(1)-Tyr(2)-Ile(3)-His(4)-Pro(5)-Phe(6)) has demonstrated potential cognitive-enhancing effects. The present investigation assessed and characterized: (1) dose-dependency of angiotensin IV's cognitive enhancement in a C57BL/6J mouse model of novel object recognition, (2) the time-course for these effects, (3) the identity of residues in the hexapeptide important to these effects and (4) the necessity of actions at angiotensin IV receptors for procognitive activity. Assessment of C57BL/6J mice in a novel object recognition task demonstrated that prior administration of angiotensin IV (0.1, 1.0, or 10.0, but not 0.01 nmol, i.c.v.) significantly enhanced novel object recognition in a dose-dependent manner. These effects were time dependent, with improved novel object recognition observed when angiotensin IV (0.1 nmol, i.c.v.) was administered 10 or 20, but not 30 min prior to the onset of the novel object recognition testing. An alanine scan of the angiotensin IV peptide revealed that replacement of the Val(1), Ile(3), His(4), or Phe(6) residues with Ala attenuated peptide-induced improvements in novel object recognition, whereas Tyr(2) or Pro(5) replacement did not significantly affect performance. Administration of the angiotensin IV receptor antagonist, divalinal-Ang IV (20 nmol, i.c.v.), reduced (but did not abolish) novel object recognition; however, this antagonist completely blocked the procognitive effects of angiotensin IV (0.1 nmol, i.c.v.) in this task. Rotorod testing demonstrated no locomotor effects with any angiotensin IV or divalinal-Ang IV dose tested. These data demonstrate that angiotensin IV produces a rapid enhancement of associative learning and memory performance in a mouse model that was dependent on the angiotensin IV receptor. Copyright © 2013 Elsevier Ltd. All rights reserved.

The relationship between protein synthesis and protein degradation in object recognition memory.

Science.gov (United States)

Furini, Cristiane R G; Myskiw, Jociane de C; Schmidt, Bianca E; Zinn, Carolina G; Peixoto, Patricia B; Pereira, Luiza D; Izquierdo, Ivan

2015-11-01

For decades there has been a consensus that de novo protein synthesis is necessary for long-term memory. A second round of protein synthesis has been described for both extinction and reconsolidation following an unreinforced test session. Recently, it was shown that consolidation and reconsolidation depend not only on protein synthesis but also on protein degradation by the ubiquitin-proteasome system (UPS), a major mechanism responsible for protein turnover. However, the involvement of UPS on consolidation and reconsolidation of object recognition memory remains unknown. Here we investigate in the CA1 region of the dorsal hippocampus the involvement of UPS-mediated protein degradation in consolidation and reconsolidation of object recognition memory. Animals with infusion cannulae stereotaxically implanted in the CA1 region of the dorsal hippocampus, were exposed to an object recognition task. The UPS inhibitor β-Lactacystin did not affect the consolidation and the reconsolidation of object recognition memory at doses known to affect other forms of memory (inhibitory avoidance, spatial learning in a water maze) while the protein synthesis inhibitor anisomycin impaired the consolidation and the reconsolidation of the object recognition memory. However, β-Lactacystin was able to reverse the impairment caused by anisomycin on the reconsolidation process in the CA1 region of the hippocampus. Therefore, it is possible to postulate a direct link between protein degradation and protein synthesis during the reconsolidation of the object recognition memory. Copyright © 2015 Elsevier B.V. All rights reserved.

The Functional Architecture of Visual Object Recognition

Science.gov (United States)

1991-07-01

different forms of agnosia can provide clues to the representations underlying normal object recognition (Farah, 1990). For example, the pair-wise...patterns of deficit and sparing occur. In a review of 99 published cases of agnosia , the observed patterns of co- occurrence implicated two underlying

Neurocomputational bases of object and face recognition.

OpenAIRE

Biederman, I; Kalocsai, P

1997-01-01

A number of behavioural phenomena distinguish the recognition of faces and objects, even when members of a set of objects are highly similar. Because faces have the same parts in approximately the same relations, individuation of faces typically requires specification of the metric variation in a holistic and integral representation of the facial surface. The direct mapping of a hypercolumn-like pattern of activation onto a representation layer that preserves relative spatial filter values in...

Random clustering ferns for multimodal object recognition

OpenAIRE

Villamizar Vergel, Michael Alejandro; Garrell Zulueta, Anais; Sanfeliu Cortés, Alberto; Moreno-Noguer, Francesc

2017-01-01

The final publication is available at link.springer.com We propose an efficient and robust method for the recognition of objects exhibiting multiple intra-class modes, where each one is associated with a particular object appearance. The proposed method, called random clustering ferns, combines synergically a single and real-time classifier, based on the boosted assembling of extremely randomized trees (ferns), with an unsupervised and probabilistic approach in order to recognize efficient...

Motor cortical processing is causally involved in object recognition.

Science.gov (United States)

Decloe, Rebecca; Obhi, Sukhvinder S

2013-12-14

Motor activity during vicarious experience of actions is a widely reported and studied phenomenon, and motor system activity also accompanies observation of graspable objects in the absence of any actions. Such motor activity is thought to reflect simulation of the observed action, or preparation to interact with the object, respectively. Here, in an initial exploratory study, we ask whether motor activity during observation of object directed actions is involved in processes related to recognition of the object after initial exposure. Single pulse Transcranial Magnetic Stimulation (TMS) was applied over the thumb representation of the motor cortex, or over the vertex, during observation of a model thumb typing on a cell-phone, and performance on a phone recognition task at the end of the trial was assessed. Disrupting motor processing over the thumb representation 100 ms after the onset of the typing video impaired the ability to recognize the phone in the recognition test, whereas there was no such effect for TMS applied over the vertex and no TMS trials. Furthermore, this effect only manifested for videos observed from the first person perspective. In an additional control condition, there was no evidence for any effects of TMS to the thumb representation or vertex when observing and recognizing non-action related shape stimuli. Overall, these data provide evidence that motor cortical processing during observation of object-directed actions from a first person perspective is causally linked to the formation of enduring representations of objects-of-action.

Spontaneous object recognition: a promising approach to the comparative study of memory

Directory of Open Access Journals (Sweden)

Rachel eBlaser

2015-07-01

Full Text Available Spontaneous recognition of a novel object is a popular measure of exploratory behavior, perception and recognition memory in rodent models. Because of its relative simplicity and speed of testing, the variety of stimuli that can be used, and its ecological validity across species, it is also an attractive task for comparative research. To date, variants of this test have been used with vertebrate and invertebrate species, but the methods have seldom been sufficiently standardized to allow cross-species comparison. Here, we review the methods necessary for the study of novel object recognition in mammalian and non-mammalian models, as well as the results of these experiments. Critical to the use of this test is an understanding of the organism’s initial response to a novel object, the modulation of exploration by context, and species differences in object perception and exploratory behaviors. We argue that with appropriate consideration of species differences in perception, object affordances, and natural exploratory behaviors, the spontaneous object recognition test can be a valid and versatile tool for translational research with non-mammalian models.

Object Recognition In HADOOP Using HIPI

Directory of Open Access Journals (Sweden)

Ankit Kumar Agrawal

2015-07-01

Full Text Available Abstract The amount of images and videos being shared by the user is exponentially increasing but applications that perform video analytics is severely lacking or work on limited set of data. It is also challenging to perform analytics with less time complexity. Object recognition is the primary step in video analytics. We implement a robust method to extract objects from the data which is in unstructured format and cannot be processed directly by relational databases. In this study we present our report with results after performance evaluation and compare them with results of MATLAB.

Improving a Deep Learning based RGB-D Object Recognition Model by Ensemble Learning

DEFF Research Database (Denmark)

Aakerberg, Andreas; Nasrollahi, Kamal; Heder, Thomas

2018-01-01

Augmenting RGB images with depth information is a well-known method to significantly improve the recognition accuracy of object recognition models. Another method to im- prove the performance of visual recognition models is ensemble learning. However, this method has not been widely explored...... in combination with deep convolutional neural network based RGB-D object recognition models. Hence, in this paper, we form different ensembles of complementary deep convolutional neural network models, and show that this can be used to increase the recognition performance beyond existing limits. Experiments...

Global precedence effects account for individual differences in both face and object recognition performance

DEFF Research Database (Denmark)

Gerlach, Christian; Starrfelt, Randi

2018-01-01

examine whether global precedence effects, measured by means of non-face stimuli in Navon's paradigm, can also account for individual differences in face recognition and, if so, whether the effect is of similar magnitude for faces and objects. We find evidence that global precedence effects facilitate...... both face and object recognition, and to a similar extent. Our results suggest that both face and object recognition are characterized by a coarse-to-fine temporal dynamic, where global shape information is derived prior to local shape information, and that the efficiency of face and object recognition...

Implementation of CT and IHT Processors for Invariant Object Recognition System

Directory of Open Access Journals (Sweden)

J. Turan jr.

2004-12-01

Full Text Available This paper presents PDL or ASIC implementation of key modules ofinvariant object recognition system based on the combination of theIncremental Hough transform (IHT, correlation and rapid transform(RT. The invariant object recognition system was represented partiallyin C++ language for general-purpose processor on personal computer andpartially described in VHDL code for implementation in PLD or ASIC.

Transformation-tolerant object recognition in rats revealed by visual priming.

Science.gov (United States)

Tafazoli, Sina; Di Filippo, Alessandro; Zoccolan, Davide

2012-01-04

Successful use of rodents as models for studying object vision crucially depends on the ability of their visual system to construct representations of visual objects that tolerate (i.e., remain relatively unchanged with respect to) the tremendous changes in object appearance produced, for instance, by size and viewpoint variation. Whether this is the case is still controversial, despite some recent demonstration of transformation-tolerant object recognition in rats. In fact, it remains unknown to what extent such a tolerant recognition has a spontaneous, perceptual basis, or, alternatively, mainly reflects learning of arbitrary associative relations among trained object appearances. In this study, we addressed this question by training rats to categorize a continuum of morph objects resulting from blending two object prototypes. The resulting psychometric curve (reporting the proportion of responses to one prototype along the morph line) served as a reference when, in a second phase of the experiment, either prototype was briefly presented as a prime, immediately before a test morph object. The resulting shift of the psychometric curve showed that recognition became biased toward the identity of the prime. Critically, this bias was observed also when the primes were transformed along a variety of dimensions (i.e., size, position, viewpoint, and their combination) that the animals had never experienced before. These results indicate that rats spontaneously perceive different views/appearances of an object as similar (i.e., as instances of the same object) and argue for the existence of neuronal substrates underlying formation of transformation-tolerant object representations in rats.

Probabilistic object and viewpoint models for active object recognition

CSIR Research Space (South Africa)

Govender, N

2013-09-01

Full Text Available ,θ′(f occ). V. EXPERIMENTS A. Dataset For our experiments, we use the active recognition dataset introduced by [12]. The training data consists of everyday objects such as cereal boxes, ornaments, spice bottle, etc. Images were captured every 20 degrees... are to be verified TABLE I CONFUSION MATRIX FOR BINARY A MODEL Obscured Obscured Obscured Obscured Obscured Obscured Obscured Obscured Obscured Obscured Cereal Battery Curry box Elephant Handbag MrMin Salad Bottle Spice Bottle Spray Can Spray Can 1 Cereal 0.9800 0...

Post-Training Reversible Inactivation of the Hippocampus Enhances Novel Object Recognition Memory

Science.gov (United States)

Oliveira, Ana M. M.; Hawk, Joshua D.; Abel, Ted; Havekes, Robbert

2010-01-01

Research on the role of the hippocampus in object recognition memory has produced conflicting results. Previous studies have used permanent hippocampal lesions to assess the requirement for the hippocampus in the object recognition task. However, permanent hippocampal lesions may impact performance through effects on processes besides memory…

Motor cortical processing is causally involved in object recognition

Science.gov (United States)

2013-01-01

Background Motor activity during vicarious experience of actions is a widely reported and studied phenomenon, and motor system activity also accompanies observation of graspable objects in the absence of any actions. Such motor activity is thought to reflect simulation of the observed action, or preparation to interact with the object, respectively. Results Here, in an initial exploratory study, we ask whether motor activity during observation of object directed actions is involved in processes related to recognition of the object after initial exposure. Single pulse Transcranial Magnetic Stimulation (TMS) was applied over the thumb representation of the motor cortex, or over the vertex, during observation of a model thumb typing on a cell-phone, and performance on a phone recognition task at the end of the trial was assessed. Disrupting motor processing over the thumb representation 100 ms after the onset of the typing video impaired the ability to recognize the phone in the recognition test, whereas there was no such effect for TMS applied over the vertex and no TMS trials. Furthermore, this effect only manifested for videos observed from the first person perspective. In an additional control condition, there was no evidence for any effects of TMS to the thumb representation or vertex when observing and recognizing non-action related shape stimuli. Conclusion Overall, these data provide evidence that motor cortical processing during observation of object-directed actions from a first person perspective is causally linked to the formation of enduring representations of objects-of-action. PMID:24330638

Dentate gyrus supports slope recognition memory, shades of grey-context pattern separation and recognition memory, and CA3 supports pattern completion for object memory.

Science.gov (United States)

Kesner, Raymond P; Kirk, Ryan A; Yu, Zhenghui; Polansky, Caitlin; Musso, Nick D

2016-03-01

In order to examine the role of the dorsal dentate gyrus (dDG) in slope (vertical space) recognition and possible pattern separation, various slope (vertical space) degrees were used in a novel exploratory paradigm to measure novelty detection for changes in slope (vertical space) recognition memory and slope memory pattern separation in Experiment 1. The results of the experiment indicate that control rats displayed a slope recognition memory function with a pattern separation process for slope memory that is dependent upon the magnitude of change in slope between study and test phases. In contrast, the dDG lesioned rats displayed an impairment in slope recognition memory, though because there was no significant interaction between the two groups and slope memory, a reliable pattern separation impairment for slope could not be firmly established in the DG lesioned rats. In Experiment 2, in order to determine whether, the dDG plays a role in shades of grey spatial context recognition and possible pattern separation, shades of grey were used in a novel exploratory paradigm to measure novelty detection for changes in the shades of grey context environment. The results of the experiment indicate that control rats displayed a shades of grey-context pattern separation effect across levels of separation of context (shades of grey). In contrast, the DG lesioned rats displayed a significant interaction between the two groups and levels of shades of grey suggesting impairment in a pattern separation function for levels of shades of grey. In Experiment 3 in order to determine whether the dorsal CA3 (dCA3) plays a role in object pattern completion, a new task requiring less training and using a choice that was based on choosing the correct set of objects on a two-choice discrimination task was used. The results indicated that control rats displayed a pattern completion function based on the availability of one, two, three or four cues. In contrast, the dCA3 lesioned rats

Figure-ground organization and object recognition processes: an interactive account.

Science.gov (United States)

Vecera, S P; O'Reilly, R C

1998-04-01

Traditional bottom-up models of visual processing assume that figure-ground organization precedes object recognition. This assumption seems logically necessary: How can object recognition occur before a region is labeled as figure? However, some behavioral studies find that familiar regions are more likely to be labeled figure than less familiar regions, a problematic finding for bottom-up models. An interactive account is proposed in which figure-ground processes receive top-down input from object representations in a hierarchical system. A graded, interactive computational model is presented that accounts for behavioral results in which familiarity effects are found. The interactive model offers an alternative conception of visual processing to bottom-up models.

Object Recognition System-on-Chip Using the Support Vector Machines

Directory of Open Access Journals (Sweden)

Houzet Dominique

2005-01-01

Full Text Available The first aim of this work is to propose the design of a system-on-chip (SoC platform dedicated to digital image and signal processing, which is tuned to implement efficiently multiply-and-accumulate (MAC vector/matrix operations. The second aim of this work is to implement a recent promising neural network method, namely, the support vector machine (SVM used for real-time object recognition, in order to build a vision machine. With such a reconfigurable and programmable SoC platform, it is possible to implement any SVM function dedicated to any object recognition problem. The final aim is to obtain an automatic reconfiguration of the SoC platform, based on the results of the learning phase on an objects' database, which makes it possible to recognize practically any object without manual programming. Recognition can be of any kind that is from image to signal data. Such a system is a general-purpose automatic classifier. Many applications can be considered as a classification problem, but are usually treated specifically in order to optimize the cost of the implemented solution. The cost of our approach is more important than a dedicated one, but in a near future, hundreds of millions of gates will be common and affordable compared to the design cost. What we are proposing here is a general-purpose classification neural network implemented on a reconfigurable SoC platform. The first version presented here is limited in size and thus in object recognition performances, but can be easily upgraded according to technology improvements.

Recognition of abstract objects via neural oscillators: interaction among topological organization, associative memory and gamma band synchronization.

Science.gov (United States)

Ursino, Mauro; Magosso, Elisa; Cuppini, Cristiano

2009-02-01

Synchronization of neural activity in the gamma band is assumed to play a significant role not only in perceptual processing, but also in higher cognitive functions. Here, we propose a neural network of Wilson-Cowan oscillators to simulate recognition of abstract objects, each represented as a collection of four features. Features are ordered in topological maps of oscillators connected via excitatory lateral synapses, to implement a similarity principle. Experience on previous objects is stored in long-range synapses connecting the different topological maps, and trained via timing dependent Hebbian learning (previous knowledge principle). Finally, a downstream decision network detects the presence of a reliable object representation, when all features are oscillating in synchrony. Simulations performed giving various simultaneous objects to the network (from 1 to 4), with some missing and/or modified properties suggest that the network can reconstruct objects, and segment them from the other simultaneously present objects, even in case of deteriorated information, noise, and moderate correlation among the inputs (one common feature). The balance between sensitivity and specificity depends on the strength of the Hebbian learning. Achieving a correct reconstruction in all cases, however, requires ad hoc selection of the oscillation frequency. The model represents an attempt to investigate the interactions among topological maps, autoassociative memory, and gamma-band synchronization, for recognition of abstract objects.

Modeling guidance and recognition in categorical search: bridging human and computer object detection.

Science.gov (United States)

Zelinsky, Gregory J; Peng, Yifan; Berg, Alexander C; Samaras, Dimitris

2013-10-08

Search is commonly described as a repeating cycle of guidance to target-like objects, followed by the recognition of these objects as targets or distractors. Are these indeed separate processes using different visual features? We addressed this question by comparing observer behavior to that of support vector machine (SVM) models trained on guidance and recognition tasks. Observers searched for a categorically defined teddy bear target in four-object arrays. Target-absent trials consisted of random category distractors rated in their visual similarity to teddy bears. Guidance, quantified as first-fixated objects during search, was strongest for targets, followed by target-similar, medium-similarity, and target-dissimilar distractors. False positive errors to first-fixated distractors also decreased with increasing dissimilarity to the target category. To model guidance, nine teddy bear detectors, using features ranging in biological plausibility, were trained on unblurred bears then tested on blurred versions of the same objects appearing in each search display. Guidance estimates were based on target probabilities obtained from these detectors. To model recognition, nine bear/nonbear classifiers, trained and tested on unblurred objects, were used to classify the object that would be fixated first (based on the detector estimates) as a teddy bear or a distractor. Patterns of categorical guidance and recognition accuracy were modeled almost perfectly by an HMAX model in combination with a color histogram feature. We conclude that guidance and recognition in the context of search are not separate processes mediated by different features, and that what the literature knows as guidance is really recognition performed on blurred objects viewed in the visual periphery.

Development of visuo-haptic transfer for object recognition in typical preschool and school-aged children.

Science.gov (United States)

Purpura, Giulia; Cioni, Giovanni; Tinelli, Francesca

2018-07-01

Object recognition is a long and complex adaptive process and its full maturation requires combination of many different sensory experiences as well as cognitive abilities to manipulate previous experiences in order to develop new percepts and subsequently to learn from the environment. It is well recognized that the transfer of visual and haptic information facilitates object recognition in adults, but less is known about development of this ability. In this study, we explored the developmental course of object recognition capacity in children using unimodal visual information, unimodal haptic information, and visuo-haptic information transfer in children from 4 years to 10 years and 11 months of age. Participants were tested through a clinical protocol, involving visual exploration of black-and-white photographs of common objects, haptic exploration of real objects, and visuo-haptic transfer of these two types of information. Results show an age-dependent development of object recognition abilities for visual, haptic, and visuo-haptic modalities. A significant effect of time on development of unimodal and crossmodal recognition skills was found. Moreover, our data suggest that multisensory processes for common object recognition are active at 4 years of age. They facilitate recognition of common objects, and, although not fully mature, are significant in adaptive behavior from the first years of age. The study of typical development of visuo-haptic processes in childhood is a starting point for future studies regarding object recognition in impaired populations.

Cultural differences in visual object recognition in 3-year-old children

Science.gov (United States)

Kuwabara, Megumi; Smith, Linda B.

2016-01-01

Recent research indicates that culture penetrates fundamental processes of perception and cognition (e.g. Nisbett & Miyamoto, 2005). Here, we provide evidence that these influences begin early and influence how preschool children recognize common objects. The three tasks (n=128) examined the degree to which nonface object recognition by 3 year olds was based on individual diagnostic features versus more configural and holistic processing. Task 1 used a 6-alternative forced choice task in which children were asked to find a named category in arrays of masked objects in which only 3 diagnostic features were visible for each object. U.S. children outperformed age-matched Japanese children. Task 2 presented pictures of objects to children piece by piece. U.S. children recognized the objects given fewer pieces than Japanese children and likelihood of recognition increased for U.S., but not Japanese children when the piece added was rated by both U.S. and Japanese adults as highly defining. Task 3 used a standard measure of configural progressing, asking the degree to which recognition of matching pictures was disrupted by the rotation of one picture. Japanese children’s recognition was more disrupted by inversion than was that of U.S. children, indicating more configural processing by Japanese than U.S. children. The pattern suggests early cross-cultural differences in visual processing; findings that raise important questions about how visual experiences differ across cultures and about universal patterns of cognitive development. PMID:26985576

Cultural differences in visual object recognition in 3-year-old children.

Science.gov (United States)

Kuwabara, Megumi; Smith, Linda B

2016-07-01

Recent research indicates that culture penetrates fundamental processes of perception and cognition. Here, we provide evidence that these influences begin early and influence how preschool children recognize common objects. The three tasks (N=128) examined the degree to which nonface object recognition by 3-year-olds was based on individual diagnostic features versus more configural and holistic processing. Task 1 used a 6-alternative forced choice task in which children were asked to find a named category in arrays of masked objects where only three diagnostic features were visible for each object. U.S. children outperformed age-matched Japanese children. Task 2 presented pictures of objects to children piece by piece. U.S. children recognized the objects given fewer pieces than Japanese children, and the likelihood of recognition increased for U.S. children, but not Japanese children, when the piece added was rated by both U.S. and Japanese adults as highly defining. Task 3 used a standard measure of configural progressing, asking the degree to which recognition of matching pictures was disrupted by the rotation of one picture. Japanese children's recognition was more disrupted by inversion than was that of U.S. children, indicating more configural processing by Japanese than U.S. children. The pattern suggests early cross-cultural differences in visual processing; findings that raise important questions about how visual experiences differ across cultures and about universal patterns of cognitive development. Copyright © 2016 Elsevier Inc. All rights reserved.

A Vision for Spaceflight Reliability: NASA's Objectives Based Strategy

Science.gov (United States)

Groen, Frank; Evans, John; Hall, Tony

2015-01-01

In defining the direction for a new Reliability and Maintainability standard, OSMA has extracted the essential objectives that our programs need, to undertake a reliable mission. These objectives have been structured to lead mission planning through construction of an objective hierarchy, which defines the critical approaches for achieving high reliability and maintainability (R M). Creating a hierarchy, as a basis for assurance implementation, is a proven approach; yet, it holds the opportunity to enable new directions, as NASA moves forward in tackling the challenges of space exploration.

Visual object recognition and category-specificity

DEFF Research Database (Denmark)

Gerlach, Christian

This thesis is based on seven published papers. The majority of the papers address two topics in visual object recognition: (i) category-effects at pre-semantic stages, and (ii) the integration of visual elements into elaborate shape descriptions corresponding to whole objects or large object parts...... (shape configuration). In the early writings these two topics were examined more or less independently. In later works, findings concerning category-effects and shape configuration merge into an integrated model, termed RACE, advanced to explain category-effects arising at pre-semantic stages in visual...... in visual long-term memory. In the thesis it is described how this simple model can account for a wide range of findings on category-specificity in both patients with brain damage and normal subjects. Finally, two hypotheses regarding the neural substrates of the model's components - and how activation...

View-invariant object recognition ability develops after discrimination, not mere exposure, at several viewing angles.

Science.gov (United States)

Yamashita, Wakayo; Wang, Gang; Tanaka, Keiji

2010-01-01

One usually fails to recognize an unfamiliar object across changes in viewing angle when it has to be discriminated from similar distractor objects. Previous work has demonstrated that after long-term experience in discriminating among a set of objects seen from the same viewing angle, immediate recognition of the objects across 30-60 degrees changes in viewing angle becomes possible. The capability for view-invariant object recognition should develop during the within-viewing-angle discrimination, which includes two kinds of experience: seeing individual views and discriminating among the objects. The aim of the present study was to determine the relative contribution of each factor to the development of view-invariant object recognition capability. Monkeys were first extensively trained in a task that required view-invariant object recognition (Object task) with several sets of objects. The animals were then exposed to a new set of objects over 26 days in one of two preparatory tasks: one in which each object view was seen individually, and a second that required discrimination among the objects at each of four viewing angles. After the preparatory period, we measured the monkeys' ability to recognize the objects across changes in viewing angle, by introducing the object set to the Object task. Results indicated significant view-invariant recognition after the second but not first preparatory task. These results suggest that discrimination of objects from distractors at each of several viewing angles is required for the development of view-invariant recognition of the objects when the distractors are similar to the objects.

Evaluating color descriptors for object and scene recognition.

Science.gov (United States)

van de Sande, Koen E A; Gevers, Theo; Snoek, Cees G M

2010-09-01

Image category recognition is important to access visual information on the level of objects and scene types. So far, intensity-based descriptors have been widely used for feature extraction at salient points. To increase illumination invariance and discriminative power, color descriptors have been proposed. Because many different descriptors exist, a structured overview is required of color invariant descriptors in the context of image category recognition. Therefore, this paper studies the invariance properties and the distinctiveness of color descriptors (software to compute the color descriptors from this paper is available from http://www.colordescriptors.com) in a structured way. The analytical invariance properties of color descriptors are explored, using a taxonomy based on invariance properties with respect to photometric transformations, and tested experimentally using a data set with known illumination conditions. In addition, the distinctiveness of color descriptors is assessed experimentally using two benchmarks, one from the image domain and one from the video domain. From the theoretical and experimental results, it can be derived that invariance to light intensity changes and light color changes affects category recognition. The results further reveal that, for light intensity shifts, the usefulness of invariance is category-specific. Overall, when choosing a single descriptor and no prior knowledge about the data set and object and scene categories is available, the OpponentSIFT is recommended. Furthermore, a combined set of color descriptors outperforms intensity-based SIFT and improves category recognition by 8 percent on the PASCAL VOC 2007 and by 7 percent on the Mediamill Challenge.

Industrial robots with sensors and object recognition systems

International Nuclear Information System (INIS)

Koehler, G.W.

1978-01-01

The previous development and the present status of industrial robots equipped with sensors and object recognition systems are described. This type of equipment allows flexible automation of many work stations in which industrial robots of the first generation, which are unable to react to changes in their respective environments automatically, apart from their being linked to other machines, could not be used because of the prevailing boundary conditions. A classification system facilitates an overview of the large number of technical solutions now available. The manifold possibilities of application of this equipment are demonstrated by a number of examples. As a result of the present state of development of the components required, and in view also of economic reasons, there is a trend towards special designs for a small number of specific purposes and towards stripped-down object recognition. systems with limited applications. A fitting description is offered of the term 'robot', which is now being used in various contexts, and an indication is made of the capabilities and components a machine to be called robot should have as a minimum. Finally, reference is made to some potential lines of development serving to reduce expediture and accelerate recognition processes. (orig.) [de

Evaluating Color Descriptors for Object and Scene Recognition

NARCIS (Netherlands)

van de Sande, K.E.A.; Gevers, T.; Snoek, C.G.M.

2010-01-01

Image category recognition is important to access visual information on the level of objects and scene types. So far, intensity-based descriptors have been widely used for feature extraction at salient points. To increase illumination invariance and discriminative power, color descriptors have been

Linguistic approach to object recognition by grasping

Energy Technology Data Exchange (ETDEWEB)

Marik, V

1982-01-01

A method for recognizing both the three-dimensional object shapes and their sizes by grasping them with an antropomorphic five-finger artificial hand is described. The hand is equipped with position sensing elements in the joints of the fingers and with a tactile transducer net on the palm surface. The linguistic method uses formal grammars and languages for the pattern description. The recognition is hierarchically arranged, every level being different from the others by a formal language which has been used. On every level the pattern description is generated and verified from the symmetrical and semantical points of view. The results of the implementation of the recognition of cones, pyramides, spheres, prisms and cylinders are presented and discussed. 8 references.

A biologically inspired neural network model to transformation invariant object recognition

Science.gov (United States)

Iftekharuddin, Khan M.; Li, Yaqin; Siddiqui, Faraz

2007-09-01

Transformation invariant image recognition has been an active research area due to its widespread applications in a variety of fields such as military operations, robotics, medical practices, geographic scene analysis, and many others. The primary goal for this research is detection of objects in the presence of image transformations such as changes in resolution, rotation, translation, scale and occlusion. We investigate a biologically-inspired neural network (NN) model for such transformation-invariant object recognition. In a classical training-testing setup for NN, the performance is largely dependent on the range of transformation or orientation involved in training. However, an even more serious dilemma is that there may not be enough training data available for successful learning or even no training data at all. To alleviate this problem, a biologically inspired reinforcement learning (RL) approach is proposed. In this paper, the RL approach is explored for object recognition with different types of transformations such as changes in scale, size, resolution and rotation. The RL is implemented in an adaptive critic design (ACD) framework, which approximates the neuro-dynamic programming of an action network and a critic network, respectively. Two ACD algorithms such as Heuristic Dynamic Programming (HDP) and Dual Heuristic dynamic Programming (DHP) are investigated to obtain transformation invariant object recognition. The two learning algorithms are evaluated statistically using simulated transformations in images as well as with a large-scale UMIST face database with pose variations. In the face database authentication case, the 90° out-of-plane rotation of faces from 20 different subjects in the UMIST database is used. Our simulations show promising results for both designs for transformation-invariant object recognition and authentication of faces. Comparing the two algorithms, DHP outperforms HDP in learning capability, as DHP takes fewer steps to

Deletion of the GluA1 AMPA receptor subunit impairs recency-dependent object recognition memory

Science.gov (United States)

Sanderson, David J.; Hindley, Emma; Smeaton, Emily; Denny, Nick; Taylor, Amy; Barkus, Chris; Sprengel, Rolf; Seeburg, Peter H.; Bannerman, David M.

2011-01-01

Deletion of the GluA1 AMPA receptor subunit impairs short-term spatial recognition memory. It has been suggested that short-term recognition depends upon memory caused by the recent presentation of a stimulus that is independent of contextual–retrieval processes. The aim of the present set of experiments was to test whether the role of GluA1 extends to nonspatial recognition memory. Wild-type and GluA1 knockout mice were tested on the standard object recognition task and a context-independent recognition task that required recency-dependent memory. In a first set of experiments it was found that GluA1 deletion failed to impair performance on either of the object recognition or recency-dependent tasks. However, GluA1 knockout mice displayed increased levels of exploration of the objects in both the sample and test phases compared to controls. In contrast, when the time that GluA1 knockout mice spent exploring the objects was yoked to control mice during the sample phase, it was found that GluA1 deletion now impaired performance on both the object recognition and the recency-dependent tasks. GluA1 deletion failed to impair performance on a context-dependent recognition task regardless of whether object exposure in knockout mice was yoked to controls or not. These results demonstrate that GluA1 is necessary for nonspatial as well as spatial recognition memory and plays an important role in recency-dependent memory processes. PMID:21378100

Object similarity affects the perceptual strategy underlying invariant visual object recognition in rats

Directory of Open Access Journals (Sweden)

Federica Bianca Rosselli

2015-03-01

Full Text Available In recent years, a number of studies have explored the possible use of rats as models of high-level visual functions. One central question at the root of such an investigation is to understand whether rat object vision relies on the processing of visual shape features or, rather, on lower-order image properties (e.g., overall brightness. In a recent study, we have shown that rats are capable of extracting multiple features of an object that are diagnostic of its identity, at least when those features are, structure-wise, distinct enough to be parsed by the rat visual system. In the present study, we have assessed the impact of object structure on rat perceptual strategy. We trained rats to discriminate between two structurally similar objects, and compared their recognition strategies with those reported in our previous study. We found that, under conditions of lower stimulus discriminability, rat visual discrimination strategy becomes more view-dependent and subject-dependent. Rats were still able to recognize the target objects, in a way that was largely tolerant (i.e., invariant to object transformation; however, the larger structural and pixel-wise similarity affected the way objects were processed. Compared to the findings of our previous study, the patterns of diagnostic features were: i smaller and more scattered; ii only partially preserved across object views; and iii only partially reproducible across rats. On the other hand, rats were still found to adopt a multi-featural processing strategy and to make use of part of the optimal discriminatory information afforded by the two objects. Our findings suggest that, as in humans, rat invariant recognition can flexibly rely on either view-invariant representations of distinctive object features or view-specific object representations, acquired through learning.

Global precedence effects account for individual differences in both face and object recognition performance.

Science.gov (United States)

Gerlach, Christian; Starrfelt, Randi

2018-03-20

There has been an increase in studies adopting an individual difference approach to examine visual cognition and in particular in studies trying to relate face recognition performance with measures of holistic processing (the face composite effect and the part-whole effect). In the present study we examine whether global precedence effects, measured by means of non-face stimuli in Navon's paradigm, can also account for individual differences in face recognition and, if so, whether the effect is of similar magnitude for faces and objects. We find evidence that global precedence effects facilitate both face and object recognition, and to a similar extent. Our results suggest that both face and object recognition are characterized by a coarse-to-fine temporal dynamic, where global shape information is derived prior to local shape information, and that the efficiency of face and object recognition is related to the magnitude of the global precedence effect.

The interplay between perceptual organization and object recognition: Temporal dynamics and neuropsychology

OpenAIRE

Torfs, Katrien

2012-01-01

The ease and efficiency with which we perceive objects in daily life masks the complexity of the processes involved. The main goal of my doctoral research was to enhance our understanding of the complex interplay between perceptual organization and object recognition. To this end, we investigated the dynamic interplay between different component processes of object recognition, and their temporal dynamics. In the first part of this thesis, I present three behavioral studies focusing on the ro...

Emerging technologies with potential for objectively evaluating speech recognition skills.

Science.gov (United States)

Rawool, Vishakha Waman

2016-01-01

Work-related exposure to noise and other ototoxins can cause damage to the cochlea, synapses between the inner hair cells, the auditory nerve fibers, and higher auditory pathways, leading to difficulties in recognizing speech. Procedures designed to determine speech recognition scores (SRS) in an objective manner can be helpful in disability compensation cases where the worker claims to have poor speech perception due to exposure to noise or ototoxins. Such measures can also be helpful in determining SRS in individuals who cannot provide reliable responses to speech stimuli, including patients with Alzheimer's disease, traumatic brain injuries, and infants with and without hearing loss. Cost-effective neural monitoring hardware and software is being rapidly refined due to the high demand for neurogaming (games involving the use of brain-computer interfaces), health, and other applications. More specifically, two related advances in neuro-technology include relative ease in recording neural activity and availability of sophisticated analysing techniques. These techniques are reviewed in the current article and their applications for developing objective SRS procedures are proposed. Issues related to neuroaudioethics (ethics related to collection of neural data evoked by auditory stimuli including speech) and neurosecurity (preservation of a person's neural mechanisms and free will) are also discussed.

A Large-Scale 3D Object Recognition dataset

DEFF Research Database (Denmark)

Sølund, Thomas; Glent Buch, Anders; Krüger, Norbert

2016-01-01

geometric groups; concave, convex, cylindrical and flat 3D object models. The object models have varying amount of local geometric features to challenge existing local shape feature descriptors in terms of descriptiveness and robustness. The dataset is validated in a benchmark which evaluates the matching...... performance of 7 different state-of-the-art local shape descriptors. Further, we validate the dataset in a 3D object recognition pipeline. Our benchmark shows as expected that local shape feature descriptors without any global point relation across the surface have a poor matching performance with flat...

Neural substrates of view-invariant object recognition developed without experiencing rotations of the objects.

Science.gov (United States)

Okamura, Jun-Ya; Yamaguchi, Reona; Honda, Kazunari; Wang, Gang; Tanaka, Keiji

2014-11-05

One fails to recognize an unfamiliar object across changes in viewing angle when it must be discriminated from similar distractor objects. View-invariant recognition gradually develops as the viewer repeatedly sees the objects in rotation. It is assumed that different views of each object are associated with one another while their successive appearance is experienced in rotation. However, natural experience of objects also contains ample opportunities to discriminate among objects at each of the multiple viewing angles. Our previous behavioral experiments showed that after experiencing a new set of object stimuli during a task that required only discrimination at each of four viewing angles at 30° intervals, monkeys could recognize the objects across changes in viewing angle up to 60°. By recording activities of neurons from the inferotemporal cortex after various types of preparatory experience, we here found a possible neural substrate for the monkeys' performance. For object sets that the monkeys had experienced during the task that required only discrimination at each of four viewing angles, many inferotemporal neurons showed object selectivity covering multiple views. The degree of view generalization found for these object sets was similar to that found for stimulus sets with which the monkeys had been trained to conduct view-invariant recognition. These results suggest that the experience of discriminating new objects in each of several viewing angles develops the partially view-generalized object selectivity distributed over many neurons in the inferotemporal cortex, which in turn bases the monkeys' emergent capability to discriminate the objects across changes in viewing angle. Copyright © 2014 the authors 0270-6474/14/3415047-13$15.00/0.

Left posterior BA37 is involved in object recognition: a TMS study

DEFF Research Database (Denmark)

Stewart, Lauren; Meyer, Bernd-Ulrich; Frith, Uta

2001-01-01

Functional imaging studies have proposed a role for left BA37 in phonological retrieval, semantic processing, face processing and object recognition. The present study targeted the posterior aspect of BA37 to see whether a deficit, specific to one of the above types of processing could be induced...... to name pictures when TMS was given over lBA37 compared to vertex or rBA37. rTMS over lBA37 had no significant effect on word reading, nonword reading or colour naming. The picture naming deficit is suggested to result from a disruption to object recognition processes. This study corroborates the finding...... from a recent imaging study, that the most posterior part of left hemispheric BA37 has a necessary role in object recognition....

Lateral septal vasopressin in rats : Role in social and object recognition?

NARCIS (Netherlands)

Everts, H.G J; Koolhaas, J.M.

1997-01-01

The capacity of male rats to remember familiar conspecifics is called social recognition. It is a form of short-term memory modulated by lateral septal (LS) vasopressin (VP). The specificity of this phenomenon was studied by examining whether recognition of previously investigated objects is also

Speckle-learning-based object recognition through scattering media.

Science.gov (United States)

Ando, Takamasa; Horisaki, Ryoichi; Tanida, Jun

2015-12-28

We experimentally demonstrated object recognition through scattering media based on direct machine learning of a number of speckle intensity images. In the experiments, speckle intensity images of amplitude or phase objects on a spatial light modulator between scattering plates were captured by a camera. We used the support vector machine for binary classification of the captured speckle intensity images of face and non-face data. The experimental results showed that speckles are sufficient for machine learning.

Online Feature Transformation Learning for Cross-Domain Object Category Recognition.

Science.gov (United States)

Zhang, Xuesong; Zhuang, Yan; Wang, Wei; Pedrycz, Witold

2017-06-09

In this paper, we introduce a new research problem termed online feature transformation learning in the context of multiclass object category recognition. The learning of a feature transformation is viewed as learning a global similarity metric function in an online manner. We first consider the problem of online learning a feature transformation matrix expressed in the original feature space and propose an online passive aggressive feature transformation algorithm. Then these original features are mapped to kernel space and an online single kernel feature transformation (OSKFT) algorithm is developed to learn a nonlinear feature transformation. Based on the OSKFT and the existing Hedge algorithm, a novel online multiple kernel feature transformation algorithm is also proposed, which can further improve the performance of online feature transformation learning in large-scale application. The classifier is trained with k nearest neighbor algorithm together with the learned similarity metric function. Finally, we experimentally examined the effect of setting different parameter values in the proposed algorithms and evaluate the model performance on several multiclass object recognition data sets. The experimental results demonstrate the validity and good performance of our methods on cross-domain and multiclass object recognition application.

Critical object recognition in millimeter-wave images with robustness to rotation and scale.

Science.gov (United States)

Mohammadzade, Hoda; Ghojogh, Benyamin; Faezi, Sina; Shabany, Mahdi

2017-06-01

Locating critical objects is crucial in various security applications and industries. For example, in security applications, such as in airports, these objects might be hidden or covered under shields or secret sheaths. Millimeter-wave images can be utilized to discover and recognize the critical objects out of the hidden cases without any health risk due to their non-ionizing features. However, millimeter-wave images usually have waves in and around the detected objects, making object recognition difficult. Thus, regular image processing and classification methods cannot be used for these images and additional pre-processings and classification methods should be introduced. This paper proposes a novel pre-processing method for canceling rotation and scale using principal component analysis. In addition, a two-layer classification method is introduced and utilized for recognition. Moreover, a large dataset of millimeter-wave images is collected and created for experiments. Experimental results show that a typical classification method such as support vector machines can recognize 45.5% of a type of critical objects at 34.2% false alarm rate (FAR), which is a drastically poor recognition. The same method within the proposed recognition framework achieves 92.9% recognition rate at 0.43% FAR, which indicates a highly significant improvement. The significant contribution of this work is to introduce a new method for analyzing millimeter-wave images based on machine vision and learning approaches, which is not yet widely noted in the field of millimeter-wave image analysis.

Object recognition in images via a factor graph model

Science.gov (United States)

He, Yong; Wang, Long; Wu, Zhaolin; Zhang, Haisu

2018-04-01

Object recognition in images suffered from huge search space and uncertain object profile. Recently, the Bag-of- Words methods are utilized to solve these problems, especially the 2-dimension CRF(Conditional Random Field) model. In this paper we suggest the method based on a general and flexible fact graph model, which can catch the long-range correlation in Bag-of-Words by constructing a network learning framework contrasted from lattice in CRF. Furthermore, we explore a parameter learning algorithm based on the gradient descent and Loopy Sum-Product algorithms for the factor graph model. Experimental results on Graz 02 dataset show that, the recognition performance of our method in precision and recall is better than a state-of-art method and the original CRF model, demonstrating the effectiveness of the proposed method.

Three-dimensional model-based object recognition and segmentation in cluttered scenes.

Science.gov (United States)

Mian, Ajmal S; Bennamoun, Mohammed; Owens, Robyn

2006-10-01

Viewpoint independent recognition of free-form objects and their segmentation in the presence of clutter and occlusions is a challenging task. We present a novel 3D model-based algorithm which performs this task automatically and efficiently. A 3D model of an object is automatically constructed offline from its multiple unordered range images (views). These views are converted into multidimensional table representations (which we refer to as tensors). Correspondences are automatically established between these views by simultaneously matching the tensors of a view with those of the remaining views using a hash table-based voting scheme. This results in a graph of relative transformations used to register the views before they are integrated into a seamless 3D model. These models and their tensor representations constitute the model library. During online recognition, a tensor from the scene is simultaneously matched with those in the library by casting votes. Similarity measures are calculated for the model tensors which receive the most votes. The model with the highest similarity is transformed to the scene and, if it aligns accurately with an object in the scene, that object is declared as recognized and is segmented. This process is repeated until the scene is completely segmented. Experiments were performed on real and synthetic data comprised of 55 models and 610 scenes and an overall recognition rate of 95 percent was achieved. Comparison with the spin images revealed that our algorithm is superior in terms of recognition rate and efficiency.

Neurophysiological indices of perceptual object priming in the absence of explicit recognition memory.

Science.gov (United States)

Harris, Jill D; Cutmore, Tim R H; O'Gorman, John; Finnigan, Simon; Shum, David

2009-02-01

The aim of this study was to identify ERP correlates of perceptual object priming that are insensitive to factors affecting explicit, episodic memory. EEG was recorded from 21 participants while they performed a visual object recognition test on a combination of unstudied items and old items that were previously encountered during either a 'deep' or 'shallow' levels-of-processing (LOP) study task. The results demonstrated a midline P150 old/new effect which was sensitive only to objects' old/new status and not to the accuracy of recognition responses to old items, or to the LOP manipulation. Similar outcomes were observed for the subsequent P200 and N400 effects, the former of which had a parietal scalp maximum and the latter, a broadly distributed topography. In addition an LPC old/new effect typical of those reported in past ERP recognition studies was observed. These outcomes support the proposal that the P150 effect is reflective of perceptual object priming and moreover, provide novel evidence that this and the P200 effect are independent of explicit recognition memory process(es).

Category-Specific Visual Recognition and Aging from the PACE Theory Perspective: Evidence for a Presemantic Deficit in Aging Object Recognition

DEFF Research Database (Denmark)

Bordaberry, Pierre; Gerlach, Christian; Lenoble, Quentin

2016-01-01

Background/Study Context: The objective of this study was to investigate the object recognition deficit in aging. Age-related declines were examined from the presemantic account of category effects (PACE) theory perspective (Gerlach, 2009, Cognition, 111, 281–301). This view assumes that the stru......Background/Study Context: The objective of this study was to investigate the object recognition deficit in aging. Age-related declines were examined from the presemantic account of category effects (PACE) theory perspective (Gerlach, 2009, Cognition, 111, 281–301). This view assumes...... that the structural similarity/dissimilarity inherent in living and nonliving objects, respectively, can account for a wide range of category-specific effects. Methods: In two experiments on object recognition, young (36 participants, 18–27 years) and older (36 participants, 53–69 years) adult participants...... in the selection stage of the PACE theory (visual long-term memory matching) could be responsible for these impairments. Indeed, the older group showed a deficit when this stage was most relevant. This article emphasize on the critical need for taking into account structural component of the stimuli and type...

Modeling guidance and recognition in categorical search: Bridging human and computer object detection

OpenAIRE

Zelinsky, Gregory J.; Peng, Yifan; Berg, Alexander C.; Samaras, Dimitris

2013-01-01

Search is commonly described as a repeating cycle of guidance to target-like objects, followed by the recognition of these objects as targets or distractors. Are these indeed separate processes using different visual features? We addressed this question by comparing observer behavior to that of support vector machine (SVM) models trained on guidance and recognition tasks. Observers searched for a categorically defined teddy bear target in four-object arrays. Target-absent trials consisted of ...

Development of novel tasks for studying view-invariant object recognition in rodents: Sensitivity to scopolamine.

Science.gov (United States)

Mitchnick, Krista A; Wideman, Cassidy E; Huff, Andrew E; Palmer, Daniel; McNaughton, Bruce L; Winters, Boyer D

2018-05-15

The capacity to recognize objects from different view-points or angles, referred to as view-invariance, is an essential process that humans engage in daily. Currently, the ability to investigate the neurobiological underpinnings of this phenomenon is limited, as few ethologically valid view-invariant object recognition tasks exist for rodents. Here, we report two complementary, novel view-invariant object recognition tasks in which rodents physically interact with three-dimensional objects. Prior to experimentation, rats and mice were given extensive experience with a set of 'pre-exposure' objects. In a variant of the spontaneous object recognition task, novelty preference for pre-exposed or new objects was assessed at various angles of rotation (45°, 90° or 180°); unlike control rodents, for whom the objects were novel, rats and mice tested with pre-exposed objects did not discriminate between rotated and un-rotated objects in the choice phase, indicating substantial view-invariant object recognition. Secondly, using automated operant touchscreen chambers, rats were tested on pre-exposed or novel objects in a pairwise discrimination task, where the rewarded stimulus (S+) was rotated (180°) once rats had reached acquisition criterion; rats tested with pre-exposed objects re-acquired the pairwise discrimination following S+ rotation more effectively than those tested with new objects. Systemic scopolamine impaired performance on both tasks, suggesting involvement of acetylcholine at muscarinic receptors in view-invariant object processing. These tasks present novel means of studying the behavioral and neural bases of view-invariant object recognition in rodents. Copyright © 2018 Elsevier B.V. All rights reserved.

Standard object recognition memory and "what" and "where" components: Improvement by post-training epinephrine in highly habituated rats.

Science.gov (United States)

Jurado-Berbel, Patricia; Costa-Miserachs, David; Torras-Garcia, Meritxell; Coll-Andreu, Margalida; Portell-Cortés, Isabel

2010-02-11

The present work examined whether post-training systemic epinephrine (EPI) is able to modulate short-term (3h) and long-term (24 h and 48 h) memory of standard object recognition, as well as long-term (24 h) memory of separate "what" (object identity) and "where" (object location) components of object recognition. Although object recognition training is associated to low arousal levels, all the animals received habituation to the training box in order to further reduce emotional arousal. Post-training EPI improved long-term (24 h and 48 h), but not short-term (3 h), memory in the standard object recognition task, as well as 24 h memory for both object identity and object location. These data indicate that post-training epinephrine: (1) facilitates long-term memory for standard object recognition; (2) exerts separate facilitatory effects on "what" (object identity) and "where" (object location) components of object recognition; and (3) is capable of improving memory for a low arousing task even in highly habituated rats.

Dopamine D4 receptor stimulation contributes to novel object recognition: Relevance to cognitive impairment in schizophrenia.

Science.gov (United States)

Miyauchi, Masanori; Neugebauer, Nichole M; Meltzer, Herbert Y

2017-04-01

Several atypical antipsychotic drugs (APDs) have high affinity for the dopamine (DA) D 4 receptor, but the relevance to the efficacy for the treatment of cognitive impairment associated with schizophrenia (CIAS) is poorly understood. The aim of this study was to investigate the effects of D 4 receptor stimulation or blockade on novel object recognition (NOR) in normal rats and on the sub-chronic phencyclidine (PCP)-induced novel object recognition deficit. The effect of the D 4 agonist, PD168077, and the D 4 antagonist, L-745,870, were studied alone, and in combination with clozapine and lurasidone. In normal rats, L-745,870 impaired novel object recognition, whereas PD168077 had no effect. PD168077 acutely reversed the sub-chronic phencyclidine-induced novel object recognition deficit. Co-administration of a sub-effective dose (SED) of PD168077 with a sub-effective dose of lurasidone also reversed this deficit, but a sub-effective dose of PD168077 with a sub-effective dose of clozapine, a more potent D 4 antagonist than lurasidone, did not reverse the sub-chronic phencyclidine-induced novel object recognition deficit. At a dose that did not induce a novel object recognition deficit, L-745,870 blocked the ability of clozapine, but not lurasidone, to reverse the novel object recognition deficit. D 4 receptor agonism has a beneficial effect on novel object recognition in sub-chronic PCP-treated rats and augments the cognitive enhancing efficacy of an atypical antipsychotic drug that lacks affinity for the D 4 receptor, lurasidone.

Object recognition using deep convolutional neural networks with complete transfer and partial frozen layers

NARCIS (Netherlands)

Kruithof, M.C.; Bouma, H.; Fischer, N.M.; Schutte, K.

2016-01-01

Object recognition is important to understand the content of video and allow flexible querying in a large number of cameras, especially for security applications. Recent benchmarks show that deep convolutional neural networks are excellent approaches for object recognition. This paper describes an

Fast and flexible 3D object recognition solutions for machine vision applications

Science.gov (United States)

Effenberger, Ira; Kühnle, Jens; Verl, Alexander

2013-03-01

In automation and handling engineering, supplying work pieces between different stages along the production process chain is of special interest. Often the parts are stored unordered in bins or lattice boxes and hence have to be separated and ordered for feeding purposes. An alternative to complex and spacious mechanical systems such as bowl feeders or conveyor belts, which are typically adapted to the parts' geometry, is using a robot to grip the work pieces out of a bin or from a belt. Such applications are in need of reliable and precise computer-aided object detection and localization systems. For a restricted range of parts, there exists a variety of 2D image processing algorithms that solve the recognition problem. However, these methods are often not well suited for the localization of randomly stored parts. In this paper we present a fast and flexible 3D object recognizer that localizes objects by identifying primitive features within the objects. Since technical work pieces typically consist to a substantial degree of geometric primitives such as planes, cylinders and cones, such features usually carry enough information in order to determine the position of the entire object. Our algorithms use 3D best-fitting combined with an intelligent data pre-processing step. The capability and performance of this approach is shown by applying the algorithms to real data sets of different industrial test parts in a prototypical bin picking demonstration system.

It's all connected: Pathways in visual object recognition and early noun learning.

Science.gov (United States)

Smith, Linda B

2013-11-01

A developmental pathway may be defined as the route, or chain of events, through which a new structure or function forms. For many human behaviors, including object name learning and visual object recognition, these pathways are often complex and multicausal and include unexpected dependencies. This article presents three principles of development that suggest the value of a developmental psychology that explicitly seeks to trace these pathways and uses empirical evidence on developmental dependencies among motor development, action on objects, visual object recognition, and object name learning in 12- to 24-month-old infants to make the case. The article concludes with a consideration of the theoretical implications of this approach. (PsycINFO Database Record (c) 2013 APA, all rights reserved).

Multi-sensor Object Recognition: The Case of Electronics Recycling

NARCIS (Netherlands)

van Dop, E.R.

1999-01-01

In automated object recognition systems, measurements from a single source of information do not always suffice for the reconstruction of the underlying scene. Incompleteness, inaccuracy and unreliability of the information often leaves room for multiple interpretations of the world which are

Communicative Signals Promote Object Recognition Memory and Modulate the Right Posterior STS.

Science.gov (United States)

Redcay, Elizabeth; Ludlum, Ruth S; Velnoskey, Kayla R; Kanwal, Simren

2016-01-01

Detection of communicative signals is thought to facilitate knowledge acquisition early in life, but less is known about the role these signals play in adult learning or about the brain systems supporting sensitivity to communicative intent. The current study examined how ostensive gaze cues and communicative actions affect adult recognition memory and modulate neural activity as measured by fMRI. For both the behavioral and fMRI experiments, participants viewed a series of videos of an actress acting on one of two objects in front of her. Communicative context in the videos was manipulated in a 2 × 2 design in which the actress either had direct gaze (Gaze) or wore a visor (NoGaze) and either pointed at (Point) or reached for (Reach) one of the objects (target) in front of her. Participants then completed a recognition memory task with old (target and nontarget) objects and novel objects. Recognition memory for target objects in the Gaze conditions was greater than NoGaze, but no effects of gesture type were seen. Similarly, the fMRI video-viewing task revealed a significant effect of Gaze within right posterior STS (pSTS), but no significant effects of Gesture. Furthermore, pSTS sensitivity to Gaze conditions was related to greater memory for objects viewed in Gaze, as compared with NoGaze, conditions. Taken together, these results demonstrate that the ostensive, communicative signal of direct gaze preceding an object-directed action enhances recognition memory for attended items and modulates the pSTS response to object-directed actions. Thus, establishment of a communicative context through ostensive signals remains an important component of learning and memory into adulthood, and the pSTS may play a role in facilitating this type of social learning.

The subjective experience of object recognition: comparing metacognition for object detection and object categorization.

Science.gov (United States)

Meuwese, Julia D I; van Loon, Anouk M; Lamme, Victor A F; Fahrenfort, Johannes J

2014-05-01

Perceptual decisions seem to be made automatically and almost instantly. Constructing a unitary subjective conscious experience takes more time. For example, when trying to avoid a collision with a car on a foggy road you brake or steer away in a reflex, before realizing you were in a near accident. This subjective aspect of object recognition has been given little attention. We used metacognition (assessed with confidence ratings) to measure subjective experience during object detection and object categorization for degraded and masked objects, while objective performance was matched. Metacognition was equal for degraded and masked objects, but categorization led to higher metacognition than did detection. This effect turned out to be driven by a difference in metacognition for correct rejection trials, which seemed to be caused by an asymmetry of the distractor stimulus: It does not contain object-related information in the detection task, whereas it does contain such information in the categorization task. Strikingly, this asymmetry selectively impacted metacognitive ability when objective performance was matched. This finding reveals a fundamental difference in how humans reflect versus act on information: When matching the amount of information required to perform two tasks at some objective level of accuracy (acting), metacognitive ability (reflecting) is still better in tasks that rely on positive evidence (categorization) than in tasks that rely more strongly on an absence of evidence (detection).

Spontaneous Object Recognition Memory in Aged Rats: Complexity versus Similarity

Science.gov (United States)

Gamiz, Fernando; Gallo, Milagros

2012-01-01

Previous work on the effect of aging on spontaneous object recognition (SOR) memory tasks in rats has yielded controversial results. Although the results at long-retention intervals are consistent, conflicting results have been reported at shorter delays. We have assessed the potential relevance of the type of object used in the performance of…

Object Recognition System in Remote Controlled Weapon Station using SIFT and SURF Methods

Directory of Open Access Journals (Sweden)

Midriem Mirdanies

2013-12-01

Full Text Available Object recognition system using computer vision that is implemented on Remote Controlled Weapon Station (RCWS is discussed. This system will make it easier to identify and shoot targeted object automatically. Algorithm was created to recognize real time multiple objects using two methods i.e. Scale Invariant Feature Transform (SIFT and Speeded Up Robust Features (SURF combined with K-Nearest Neighbors (KNN and Random Sample Consensus (RANSAC for verification. The algorithm is designed to improve object detection to be more robust and to minimize the processing time required. Objects are registered on the system consisting of the armored personnel carrier, tanks, bus, sedan, big foot, and police jeep. In addition, object selection can use mouse to shoot another object that has not been registered on the system. Kinect™ is used to capture RGB images and to find the coordinates x, y, and z of the object. The programming language used is C with visual studio IDE 2010 and opencv libraries. Object recognition program is divided into three parts: 1 reading image from kinect™ and simulation results, 2 object recognition process, and 3 transfer of the object data to the ballistic computer. Communication between programs is performed using shared memory. The detected object data is sent to the ballistic computer via Local Area Network (LAN using winsock for ballistic calculation, and then the motor control system moves the direction of the weapon model to the desired object. The experimental results show that the SIFT method is more suitable because more accurate and faster than SURF with the average processing time to detect one object is 430.2 ms, two object is 618.4 ms, three objects is 682.4 ms, and four objects is 756.2 ms. Object recognition program is able to recognize multi-objects and the data of the identified object can be processed by the ballistic computer in realtime.

Neuropeptide S interacts with the basolateral amygdala noradrenergic system in facilitating object recognition memory consolidation.

Science.gov (United States)

Han, Ren-Wen; Xu, Hong-Jiao; Zhang, Rui-San; Wang, Pei; Chang, Min; Peng, Ya-Li; Deng, Ke-Yu; Wang, Rui

2014-01-01

The noradrenergic activity in the basolateral amygdala (BLA) was reported to be involved in the regulation of object recognition memory. As the BLA expresses high density of receptors for Neuropeptide S (NPS), we investigated whether the BLA is involved in mediating NPS's effects on object recognition memory consolidation and whether such effects require noradrenergic activity. Intracerebroventricular infusion of NPS (1nmol) post training facilitated 24-h memory in a mouse novel object recognition task. The memory-enhancing effect of NPS could be blocked by the β-adrenoceptor antagonist propranolol. Furthermore, post-training intra-BLA infusions of NPS (0.5nmol/side) improved 24-h memory for objects, which was impaired by co-administration of propranolol (0.5μg/side). Taken together, these results indicate that NPS interacts with the BLA noradrenergic system in improving object recognition memory during consolidation. Copyright © 2013 Elsevier Inc. All rights reserved.

Dopamine D1 receptor activation leads to object recognition memory in a coral reef fish.

Science.gov (United States)

Hamilton, Trevor J; Tresguerres, Martin; Kline, David I

2017-07-01

Object recognition memory is the ability to identify previously seen objects and is an adaptive mechanism that increases survival for many species throughout the animal kingdom. Previously believed to be possessed by only the highest order mammals, it is now becoming clear that fish are also capable of this type of memory formation. Similar to the mammalian hippocampus, the dorsolateral pallium regulates distinct memory processes and is modulated by neurotransmitters such as dopamine. Caribbean bicolour damselfish ( Stegastes partitus ) live in complex environments dominated by coral reef structures and thus likely possess many types of complex memory abilities including object recognition. This study used a novel object recognition test in which fish were first presented two identical objects, then after a retention interval of 10 min with no objects, the fish were presented with a novel object and one of the objects they had previously encountered in the first trial. We demonstrate that the dopamine D 1 -receptor agonist (SKF 38393) induces the formation of object recognition memories in these fish. Thus, our results suggest that dopamine-receptor mediated enhancement of spatial memory formation in fish represents an evolutionarily conserved mechanism in vertebrates. © 2017 The Author(s).

Contextual System of Symbol Structural Recognition based on an Object-Process Methodology

OpenAIRE

Delalandre, Mathieu

2005-01-01

We present in this paper a symbol recognition system for the graphic documents. This one is based on a contextual approach for symbol structural recognition exploiting an Object-Process Methodology. It uses a processing library composed of structural recognition processings and contextual evaluation processings. These processings allow our system to deal with the multi-representation of symbols. The different processings are controlled, in an automatic way, by an inference engine during the r...

Incremental support vector machines for fast reliable image recognition

International Nuclear Information System (INIS)

Makili, L.; Vega, J.; Dormido-Canto, S.

2013-01-01

Highlights: ► A conformal predictor using SVM as the underlying algorithm was implemented. ► It was applied to image recognition in the TJ–II's Thomson Scattering Diagnostic. ► To improve time efficiency an approach to incremental SVM training has been used. ► Accuracy is similar to the one reached when standard SVM is used. ► Computational time saving is significant for large training sets. -- Abstract: This paper addresses the reliable classification of images in a 5-class problem. To this end, an automatic recognition system, based on conformal predictors and using Support Vector Machines (SVM) as the underlying algorithm has been developed and applied to the recognition of images in the Thomson Scattering Diagnostic of the TJ–II fusion device. Using such conformal predictor based classifier is a computationally intensive task since it implies to train several SVM models to classify a single example and to perform this training from scratch takes a significant amount of time. In order to improve the classification time efficiency, an approach to the incremental training of SVM has been used as the underlying algorithm. Experimental results show that the overall performance of the new classifier is high, comparable to the one corresponding to the use of standard SVM as the underlying algorithm and there is a significant improvement in time efficiency

Incremental support vector machines for fast reliable image recognition

Energy Technology Data Exchange (ETDEWEB)

Makili, L., E-mail: makili_le@yahoo.com [Instituto Superior Politécnico da Universidade Katyavala Bwila, Benguela (Angola); Vega, J. [Asociación EURATOM/CIEMAT para Fusión, Madrid (Spain); Dormido-Canto, S. [Dpto. Informática y Automática – UNED, Madrid (Spain)

2013-10-15

Highlights: ► A conformal predictor using SVM as the underlying algorithm was implemented. ► It was applied to image recognition in the TJ–II's Thomson Scattering Diagnostic. ► To improve time efficiency an approach to incremental SVM training has been used. ► Accuracy is similar to the one reached when standard SVM is used. ► Computational time saving is significant for large training sets. -- Abstract: This paper addresses the reliable classification of images in a 5-class problem. To this end, an automatic recognition system, based on conformal predictors and using Support Vector Machines (SVM) as the underlying algorithm has been developed and applied to the recognition of images in the Thomson Scattering Diagnostic of the TJ–II fusion device. Using such conformal predictor based classifier is a computationally intensive task since it implies to train several SVM models to classify a single example and to perform this training from scratch takes a significant amount of time. In order to improve the classification time efficiency, an approach to the incremental training of SVM has been used as the underlying algorithm. Experimental results show that the overall performance of the new classifier is high, comparable to the one corresponding to the use of standard SVM as the underlying algorithm and there is a significant improvement in time efficiency.

A General Polygon-based Deformable Model for Object Recognition

DEFF Research Database (Denmark)

Jensen, Rune Fisker; Carstensen, Jens Michael

1999-01-01

We propose a general scheme for object localization and recognition based on a deformable model. The model combines shape and image properties by warping a arbitrary prototype intensity template according to the deformation in shape. The shape deformations are constrained by a probabilistic distr...

Enriched environment effects on remote object recognition memory.

Science.gov (United States)

Melani, Riccardo; Chelini, Gabriele; Cenni, Maria Cristina; Berardi, Nicoletta

2017-06-03

Since Ebbinghaus' classical work on oblivion and saving effects, we know that declarative memories may become at first spontaneously irretrievable and only subsequently completely extinguished. Recently, this time-dependent path toward memory-trace loss has been shown to correlate with different patterns of brain activation. Environmental enrichment (EE) enhances learning and memory and affects system memory consolidation. However, there is no evidence on whether and how EE could affect the time-dependent path toward oblivion. We used Object Recognition Test (ORT) to assess in adult mice put in EE for 40days (EE mice) or left in standard condition (SC mice) memory retrieval of the familiar objects 9 and 21days after learning with or without a brief retraining performed the day before. We found that SC mice show preferential exploration of new object at day 9 only with retraining, while EE mice do it even without. At day 21 SC mice do not show preferential exploration of novel object, irrespective of the retraining, while EE mice are still capable to benefit from retraining, even if they were not able to spontaneously recover the trace. Analysis of c-fos expression 20days after learning shows a different pattern of active brain areas in response to the retraining session in EE and SC mice, with SC mice recruiting the same brain network as naïve SC or EE mice following de novo learning. This suggests that EE promotes formation of longer lasting object recognition memory, allowing a longer time window during which saving is present. Copyright © 2017 IBRO. Published by Elsevier Ltd. All rights reserved.

An Approach to Object Recognition: Aligning Pictorial Descriptions.

Science.gov (United States)

1986-12-01

PERFORMING 0RGANIZATION NAMIE ANDORS IS551. PROGRAM ELEMENT. PROJECT. TASK Artificial Inteligence Laboratory AREKA A WORK UNIT NUMBERS ( 545 Technology... ARTIFICIAL INTELLIGENCE LABORATORY A.I. Memo No. 931 December, 1986 AN APPROACH TO OBJECT RECOGNITION: ALIGNING PICTORIAL DESCRIPTIONS Shimon Ullman...within the Artificial Intelligence Laboratory at the Massachusetts Institute of Technology. Support for the A.I. Laboratory’s artificial intelligence

Attentional Selection for Object Recognition - A Gentle Way

National Research Council Canada - National Science Library

Walther, Dirk; Itti, Laurent; Riesenhuber, Maximilian; Poggio, Tomaso; Koch, Christof

2002-01-01

...% at a high level is sufficient to recognize multiple objects. To determine the size and shape of the region to be modulated, a rough segmentation is performed, based on pre-attentive features already computed to guide attention. Testing with synthetic and natural stimuli demonstrates that our new approach to attentional selection for recognition yields encouraging results in addition to being biologically plausible.

Dorsal stream involvement in recognition of objects with transient onset but not with ramped onset

Directory of Open Access Journals (Sweden)

Lourenco Tomas

2011-08-01

Full Text Available Abstract Background Although the ventral visual stream is understood to be responsible for object recognition, it has been proposed that the dorsal stream may contribute to object recognition by rapidly activating parietal attention mechanisms, prior to ventral stream object processing. Methods To investigate the relative contribution of the dorsal visual stream to object recognition a group of tertiary students were divided into good and poor motion coherence groups and assessed on tasks classically assumed to rely on ventral stream processing. Participants were required to identify simple line drawings in two tasks, one where objects were presented abruptly for 50 ms followed by a white-noise mask, the other where contrast was linearly ramped on and off over 325 ms and replaced with a mask. Results Although both groups only differed in motion coherence performance (a dorsal stream measure, the good motion coherence group showed superior contrast sensitivity for object recognition on the abrupt, but not the ramped presentation tasks. Conclusions We propose that abrupt presentation of objects activated attention mechanisms fed by the dorsal stream, whereas the ramped presentation had reduced transience and thus did not activate dorsal attention mechanisms as well. The results suggest that rapid dorsal stream activation may be required to assist with ventral stream object processing.

Computing with Connections in Visual Recognition of Origami Objects.

Science.gov (United States)

Sabbah, Daniel

1985-01-01

Summarizes an initial foray in tackling artificial intelligence problems using a connectionist approach. The task chosen is visual recognition of Origami objects, and the questions answered are how to construct a connectionist network to represent and recognize projected Origami line drawings and the advantages such an approach would have. (30…

Early age-dependent impairments of context-dependent extinction learning, object recognition, and object-place learning occur in rats.

Science.gov (United States)

Wiescholleck, Valentina; Emma André, Marion Agnès; Manahan-Vaughan, Denise

2014-03-01

The hippocampus is vulnerable to age-dependent memory decline. Multiple forms of memory depend on adequate hippocampal function. Extinction learning comprises active inhibition of no longer relevant learned information concurrent with suppression of a previously learned reaction. It is highly dependent on context, and evidence exists that it requires hippocampal activation. In this study, we addressed whether context-based extinction as well as hippocampus-dependent tasks, such as object recognition and object-place recognition, are equally affected by moderate aging. Young (7-8 week old) and older (7-8 month old) Wistar rats were used. For the extinction study, animals learned that a particular floor context indicated that they should turn into one specific arm (e.g., left) to receive a food reward. On the day after reaching the learning criterion of 80% correct choices, the floor context was changed, no reward was given and animals were expected to extinguish the learned response. Both, young and older rats managed this first extinction trial in the new context with older rats showing a faster extinction performance. One day later, animals were returned to the T-maze with the original floor context and renewal effects were assessed. In this case, only young but not older rats showed the expected renewal effect (lower extinction ratio as compared to the day before). To assess general memory abilities, animals were tested in the standard object recognition and object-place memory tasks. Evaluations were made at 5 min, 1 h and 7 day intervals. Object recognition memory was poor at short-term and intermediate time-points in older but not young rats. Object-place memory performance was unaffected at 5 min, but impaired at 1 h in older but not young rats. Both groups were impaired at 7 days. These findings support that not only aspects of general memory, but also context-dependent extinction learning, are affected by moderate aging. This may reflect less flexibility in

Neural network application for thermal image recognition of low-resolution objects

Science.gov (United States)

Fang, Yi-Chin; Wu, Bo-Wen

2007-02-01

In the ever-changing situation on a battle field, accurate recognition of a distant object is critical to a commander's decision-making and the general public's safety. Efficiently distinguishing between an enemy's armoured vehicles and ordinary civilian houses under all weather conditions has become an important research topic. This study presents a system for recognizing an armoured vehicle by distinguishing marks and contours. The characteristics of 12 different shapes and 12 characters are used to explore thermal image recognition under the circumstance of long distance and low resolution. Although the recognition capability of human eyes is superior to that of artificial intelligence under normal conditions, it tends to deteriorate substantially under long-distance and low-resolution scenarios. This study presents an effective method for choosing features and processing images. The artificial neural network technique is applied to further improve the probability of accurate recognition well beyond the limit of the recognition capability of human eyes.

The Consolidation of Object and Context Recognition Memory Involve Different Regions of the Temporal Lobe

Science.gov (United States)

Balderas, Israela; Rodriguez-Ortiz, Carlos J.; Salgado-Tonda, Paloma; Chavez-Hurtado, Julio; McGaugh, James L.; Bermudez-Rattoni, Federico

2008-01-01

These experiments investigated the involvement of several temporal lobe regions in consolidation of recognition memory. Anisomycin, a protein synthesis inhibitor, was infused into the hippocampus, perirhinal cortex, insular cortex, or basolateral amygdala of rats immediately after the sample phase of object or object-in-context recognition memory…

Metric invariance in object recognition: a review and further evidence.

Science.gov (United States)

Cooper, E E; Biederman, I; Hummel, J E

1992-06-01

Phenomenologically, human shape recognition appears to be invariant with changes of orientation in depth (up to parts occlusion), position in the visual field, and size. Recent versions of template theories (e.g., Ullman, 1989; Lowe, 1987) assume that these invariances are achieved through the application of transformations such as rotation, translation, and scaling of the image so that it can be matched metrically to a stored template. Presumably, such transformations would require time for their execution. We describe recent priming experiments in which the effects of a prior brief presentation of an image on its subsequent recognition are assessed. The results of these experiments indicate that the invariance is complete: The magnitude of visual priming (as distinct from name or basic level concept priming) is not affected by a change in position, size, orientation in depth, or the particular lines and vertices present in the image, as long as representations of the same components can be activated. An implemented seven layer neural network model (Hummel & Biederman, 1992) that captures these fundamental properties of human object recognition is described. Given a line drawing of an object, the model activates a viewpoint-invariant structural description of the object, specifying its parts and their interrelations. Visual priming is interpreted as a change in the connection weights for the activation of: a) cells, termed geon feature assemblies (GFAs), that conjoin the output of units that represent invariant, independent properties of a single geon and its relations (such as its type, aspect ratio, relations to other geons), or b) a change in the connection weights by which several GFAs activate a cell representing an object.

An Adaptive Classification Strategy for Reliable Locomotion Mode Recognition

Directory of Open Access Journals (Sweden)

Ming Liu

2017-09-01

Full Text Available Algorithms for locomotion mode recognition (LMR based on surface electromyography and mechanical sensors have recently been developed and could be used for the neural control of powered prosthetic legs. However, the variations in input signals, caused by physical changes at the sensor interface and human physiological changes, may threaten the reliability of these algorithms. This study aimed to investigate the effectiveness of applying adaptive pattern classifiers for LMR. Three adaptive classifiers, i.e., entropy-based adaptation (EBA, LearnIng From Testing data (LIFT, and Transductive Support Vector Machine (TSVM, were compared and offline evaluated using data collected from two able-bodied subjects and one transfemoral amputee. The offline analysis indicated that the adaptive classifier could effectively maintain or restore the performance of the LMR algorithm when gradual signal variations occurred. EBA and LIFT were recommended because of their better performance and higher computational efficiency. Finally, the EBA was implemented for real-time human-in-the-loop prosthesis control. The online evaluation showed that the applied EBA effectively adapted to changes in input signals across sessions and yielded more reliable prosthesis control over time, compared with the LMR without adaptation. The developed novel adaptive strategy may further enhance the reliability of neurally-controlled prosthetic legs.

Glucocorticoid effects on object recognition memory require training-associated emotional arousal.

Science.gov (United States)

Okuda, Shoki; Roozendaal, Benno; McGaugh, James L

2004-01-20

Considerable evidence implicates glucocorticoid hormones in the regulation of memory consolidation and memory retrieval. The present experiments investigated whether the influence of these hormones on memory depends on the level of emotional arousal induced by the training experience. We investigated this issue in male Sprague-Dawley rats by examining the effects of immediate posttraining systemic injections of the glucocorticoid corticosterone on object recognition memory under two conditions that differed in their training-associated emotional arousal. In rats that were not previously habituated to the experimental context, corticosterone (0.3, 1.0, or 3.0 mg/kg, s.c.) administered immediately after a 3-min training trial enhanced 24-hr retention performance in an inverted-U shaped dose-response relationship. In contrast, corticosterone did not affect 24-hr retention of rats that received extensive prior habituation to the experimental context and, thus, had decreased novelty-induced emotional arousal during training. Additionally, immediate posttraining administration of corticosterone to nonhabituated rats, in doses that enhanced 24-hr retention, impaired object recognition performance at a 1-hr retention interval whereas corticosterone administered after training to well-habituated rats did not impair 1-hr retention. Thus, the present findings suggest that training-induced emotional arousal may be essential for glucocorticoid effects on object recognition memory.

Optimization of constrained multiple-objective reliability problems using evolutionary algorithms

International Nuclear Information System (INIS)

Salazar, Daniel; Rocco, Claudio M.; Galvan, Blas J.

2006-01-01

This paper illustrates the use of multi-objective optimization to solve three types of reliability optimization problems: to find the optimal number of redundant components, find the reliability of components, and determine both their redundancy and reliability. In general, these problems have been formulated as single objective mixed-integer non-linear programming problems with one or several constraints and solved by using mathematical programming techniques or special heuristics. In this work, these problems are reformulated as multiple-objective problems (MOP) and then solved by using a second-generation Multiple-Objective Evolutionary Algorithm (MOEA) that allows handling constraints. The MOEA used in this paper (NSGA-II) demonstrates the ability to identify a set of optimal solutions (Pareto front), which provides the Decision Maker with a complete picture of the optimal solution space. Finally, the advantages of both MOP and MOEA approaches are illustrated by solving four redundancy problems taken from the literature

Optimization of constrained multiple-objective reliability problems using evolutionary algorithms

Energy Technology Data Exchange (ETDEWEB)

Salazar, Daniel [Instituto de Sistemas Inteligentes y Aplicaciones Numericas en Ingenieria (IUSIANI), Division de Computacion Evolutiva y Aplicaciones (CEANI), Universidad de Las Palmas de Gran Canaria, Islas Canarias (Spain) and Facultad de Ingenieria, Universidad Central Venezuela, Caracas (Venezuela)]. E-mail: danielsalazaraponte@gmail.com; Rocco, Claudio M. [Facultad de Ingenieria, Universidad Central Venezuela, Caracas (Venezuela)]. E-mail: crocco@reacciun.ve; Galvan, Blas J. [Instituto de Sistemas Inteligentes y Aplicaciones Numericas en Ingenieria (IUSIANI), Division de Computacion Evolutiva y Aplicaciones (CEANI), Universidad de Las Palmas de Gran Canaria, Islas Canarias (Spain)]. E-mail: bgalvan@step.es

2006-09-15

This paper illustrates the use of multi-objective optimization to solve three types of reliability optimization problems: to find the optimal number of redundant components, find the reliability of components, and determine both their redundancy and reliability. In general, these problems have been formulated as single objective mixed-integer non-linear programming problems with one or several constraints and solved by using mathematical programming techniques or special heuristics. In this work, these problems are reformulated as multiple-objective problems (MOP) and then solved by using a second-generation Multiple-Objective Evolutionary Algorithm (MOEA) that allows handling constraints. The MOEA used in this paper (NSGA-II) demonstrates the ability to identify a set of optimal solutions (Pareto front), which provides the Decision Maker with a complete picture of the optimal solution space. Finally, the advantages of both MOP and MOEA approaches are illustrated by solving four redundancy problems taken from the literature.

Priming Contour-Deleted Images: Evidence for Immediate Representations in Visual Object Recognition.

Science.gov (United States)

Biederman, Irving; Cooper, Eric E.

1991-01-01

Speed and accuracy of identification of pictures of objects are facilitated by prior viewing. Contributions of image features, convex or concave components, and object models in a repetition priming task were explored in 2 studies involving 96 college students. Results provide evidence of intermediate representations in visual object recognition.…

Recurrent Convolutional Neural Networks: A Better Model of Biological Object Recognition.

Science.gov (United States)

Spoerer, Courtney J; McClure, Patrick; Kriegeskorte, Nikolaus

2017-01-01

Feedforward neural networks provide the dominant model of how the brain performs visual object recognition. However, these networks lack the lateral and feedback connections, and the resulting recurrent neuronal dynamics, of the ventral visual pathway in the human and non-human primate brain. Here we investigate recurrent convolutional neural networks with bottom-up (B), lateral (L), and top-down (T) connections. Combining these types of connections yields four architectures (B, BT, BL, and BLT), which we systematically test and compare. We hypothesized that recurrent dynamics might improve recognition performance in the challenging scenario of partial occlusion. We introduce two novel occluded object recognition tasks to test the efficacy of the models, digit clutter (where multiple target digits occlude one another) and digit debris (where target digits are occluded by digit fragments). We find that recurrent neural networks outperform feedforward control models (approximately matched in parametric complexity) at recognizing objects, both in the absence of occlusion and in all occlusion conditions. Recurrent networks were also found to be more robust to the inclusion of additive Gaussian noise. Recurrent neural networks are better in two respects: (1) they are more neurobiologically realistic than their feedforward counterparts; (2) they are better in terms of their ability to recognize objects, especially under challenging conditions. This work shows that computer vision can benefit from using recurrent convolutional architectures and suggests that the ubiquitous recurrent connections in biological brains are essential for task performance.

Distinct roles of basal forebrain cholinergic neurons in spatial and object recognition memory

OpenAIRE

Kana Okada; Kayo Nishizawa; Tomoko Kobayashi; Shogo Sakata; Kazuto Kobayashi

2015-01-01

Recognition memory requires processing of various types of information such as objects and locations. Impairment in recognition memory is a prominent feature of amnesia and a symptom of Alzheimer?s disease (AD). Basal forebrain cholinergic neurons contain two major groups, one localized in the medial septum (MS)/vertical diagonal band of Broca (vDB), and the other in the nucleus basalis magnocellularis (NBM). The roles of these cell groups in recognition memory have been debated, and it remai...

A rat in the sewer: How mental imagery interacts with object recognition.

Science.gov (United States)

Karimpur, Harun; Hamburger, Kai

2018-01-01

The role of mental imagery has been puzzling researchers for more than two millennia. Both positive and negative effects of mental imagery on information processing have been discussed. The aim of this work was to examine how mental imagery affects object recognition and associative learning. Based on different perceptual and cognitive accounts we tested our imagery-induced interaction hypothesis in a series of two experiments. According to that, mental imagery could lead to (1) a superior performance in object recognition and associative learning if these objects are imagery-congruent (semantically) and to (2) an inferior performance if these objects are imagery-incongruent. In the first experiment, we used a static environment and tested associative learning. In the second experiment, subjects encoded object information in a dynamic environment by means of a virtual sewer system. Our results demonstrate that subjects who received a role adoption task (by means of guided mental imagery) performed better when imagery-congruent objects were used and worse when imagery-incongruent objects were used. We finally discuss our findings also with respect to alternative accounts and plead for a multi-methodological approach for future research in order to solve this issue.

Structured Kernel Dictionary Learning with Correlation Constraint for Object Recognition.

Science.gov (United States)

Wang, Zhengjue; Wang, Yinghua; Liu, Hongwei; Zhang, Hao

2017-06-21

In this paper, we propose a new discriminative non-linear dictionary learning approach, called correlation constrained structured kernel KSVD, for object recognition. The objective function for dictionary learning contains a reconstructive term and a discriminative term. In the reconstructive term, signals are implicitly non-linearly mapped into a space, where a structured kernel dictionary, each sub-dictionary of which lies in the span of the mapped signals from the corresponding class, is established. In the discriminative term, by analyzing the classification mechanism, the correlation constraint is proposed in kernel form, constraining the correlations between different discriminative codes, and restricting the coefficient vectors to be transformed into a feature space, where the features are highly correlated inner-class and nearly independent between-classes. The objective function is optimized by the proposed structured kernel KSVD. During the classification stage, the specific form of the discriminative feature is needless to be known, while the inner product of the discriminative feature with kernel matrix embedded is available, and is suitable for a linear SVM classifier. Experimental results demonstrate that the proposed approach outperforms many state-of-the-art dictionary learning approaches for face, scene and synthetic aperture radar (SAR) vehicle target recognition.

A Neural Model Combining Attentional Orienting to Object Recognition: Preliminary Explorations on the Interplay Between Where and What

National Research Council Canada - National Science Library

Miau, Florence

2001-01-01

... ("where") pathway and an object recognition ("what") pathway. The fast visual attention front-end rapidly selects the few most conspicuous image locations, and the slower object recognition back-end identifies objects at the selected locations...

Discriminative kernel feature extraction and learning for object recognition and detection

DEFF Research Database (Denmark)

Pan, Hong; Olsen, Søren Ingvor; Zhu, Yaping

2015-01-01

Feature extraction and learning is critical for object recognition and detection. By embedding context cue of image attributes into the kernel descriptors, we propose a set of novel kernel descriptors called context kernel descriptors (CKD). The motivation of CKD is to use the spatial consistency...... even in high-dimensional space. In addition, the latent connection between Rényi quadratic entropy and the mapping data in kernel feature space further facilitates us to capture the geometric structure as well as the information about the underlying labels of the CKD using CSQMI. Thus the resulting...... codebook and reduced CKD are discriminative. We report superior performance of our algorithm for object recognition on benchmark datasets like Caltech-101 and CIFAR-10, as well as for detection on a challenging chicken feet dataset....

Crowded and Sparse Domains in Object Recognition: Consequences for Categorization and Naming

Science.gov (United States)

Gale, Tim M.; Laws, Keith R.; Foley, Kerry

2006-01-01

Some models of object recognition propose that items from structurally crowded categories (e.g., living things) permit faster access to superordinate semantic information than structurally dissimilar categories (e.g., nonliving things), but slower access to individual object information when naming items. We present four experiments that utilize…

Face Recognition Is Affected by Similarity in Spatial Frequency Range to a Greater Degree Than Within-Category Object Recognition

Science.gov (United States)

Collin, Charles A.; Liu, Chang Hong; Troje, Nikolaus F.; McMullen, Patricia A.; Chaudhuri, Avi

2004-01-01

Previous studies have suggested that face identification is more sensitive to variations in spatial frequency content than object recognition, but none have compared how sensitive the 2 processes are to variations in spatial frequency overlap (SFO). The authors tested face and object matching accuracy under varying SFO conditions. Their results…

A field study of the accuracy and reliability of a biometric iris recognition system.

Science.gov (United States)

Latman, Neal S; Herb, Emily

2013-06-01

The iris of the eye appears to satisfy the criteria for a good anatomical characteristic for use in a biometric system. The purpose of this study was to evaluate a biometric iris recognition system: Mobile-Eyes™. The enrollment, verification, and identification applications were evaluated in a field study for accuracy and reliability using both irises of 277 subjects. Independent variables included a wide range of subject demographics, ambient light, and ambient temperature. A sub-set of 35 subjects had alcohol-induced nystagmus. There were 2710 identification and verification attempts, which resulted in 1,501,340 and 5540 iris comparisons respectively. In this study, the system successfully enrolled all subjects on the first attempt. All 277 subjects were successfully verified and identified on the first day of enrollment. None of the current or prior eye conditions prevented enrollment, verification, or identification. All 35 subjects with alcohol-induced nystagmus were successfully verified and identified. There were no false verifications or false identifications. Two conditions were identified that potentially could circumvent the use of iris recognitions systems in general. The Mobile-Eyes™ iris recognition system exhibited accurate and reliable enrollment, verification, and identification applications in this study. It may have special applications in subjects with nystagmus. Copyright © 2012 Forensic Science Society. Published by Elsevier Ireland Ltd. All rights reserved.

Enhancing Perception with Tactile Object Recognition in Adaptive Grippers for Human–Robot Interaction

Directory of Open Access Journals (Sweden)

Juan M. Gandarias

2018-02-01

Full Text Available The use of tactile perception can help first response robotic teams in disaster scenarios, where visibility conditions are often reduced due to the presence of dust, mud, or smoke, distinguishing human limbs from other objects with similar shapes. Here, the integration of the tactile sensor in adaptive grippers is evaluated, measuring the performance of an object recognition task based on deep convolutional neural networks (DCNNs using a flexible sensor mounted in adaptive grippers. A total of 15 classes with 50 tactile images each were trained, including human body parts and common environment objects, in semi-rigid and flexible adaptive grippers based on the fin ray effect. The classifier was compared against the rigid configuration and a support vector machine classifier (SVM. Finally, a two-level output network has been proposed to provide both object-type recognition and human/non-human classification. Sensors in adaptive grippers have a higher number of non-null tactels (up to 37% more, with a lower mean of pressure values (up to 72% less than when using a rigid sensor, with a softer grip, which is needed in physical human–robot interaction (pHRI. A semi-rigid implementation with 95.13% object recognition rate was chosen, even though the human/non-human classification had better results (98.78% with a rigid sensor.

Enhancing Perception with Tactile Object Recognition in Adaptive Grippers for Human-Robot Interaction.

Science.gov (United States)

Gandarias, Juan M; Gómez-de-Gabriel, Jesús M; García-Cerezo, Alfonso J

2018-02-26

The use of tactile perception can help first response robotic teams in disaster scenarios, where visibility conditions are often reduced due to the presence of dust, mud, or smoke, distinguishing human limbs from other objects with similar shapes. Here, the integration of the tactile sensor in adaptive grippers is evaluated, measuring the performance of an object recognition task based on deep convolutional neural networks (DCNNs) using a flexible sensor mounted in adaptive grippers. A total of 15 classes with 50 tactile images each were trained, including human body parts and common environment objects, in semi-rigid and flexible adaptive grippers based on the fin ray effect. The classifier was compared against the rigid configuration and a support vector machine classifier (SVM). Finally, a two-level output network has been proposed to provide both object-type recognition and human/non-human classification. Sensors in adaptive grippers have a higher number of non-null tactels (up to 37% more), with a lower mean of pressure values (up to 72% less) than when using a rigid sensor, with a softer grip, which is needed in physical human-robot interaction (pHRI). A semi-rigid implementation with 95.13% object recognition rate was chosen, even though the human/non-human classification had better results (98.78%) with a rigid sensor.

Reliability of automatic biometric iris recognition after phacoemulsification or drug-induced pupil dilation.

Science.gov (United States)

Seyeddain, Orang; Kraker, Hannes; Redlberger, Andreas; Dexl, Alois K; Grabner, Günther; Emesz, Martin

2014-01-01

To investigate the reliability of a biometric iris recognition system for personal authentication after cataract surgery or iatrogenic pupil dilation. This was a prospective, nonrandomized, single-center, cohort study for evaluating the performance of an iris recognition system 2-24 hours after phacoemulsification and intraocular lens implantation (group 1) and before and after iatrogenic pupil dilation (group 2). Of the 173 eyes that could be enrolled before cataract surgery, 164 (94.8%) were easily recognized postoperatively, whereas in 9 (5.2%) this was not possible. However, these 9 eyes could be reenrolled and afterwards recognized successfully. In group 2, of a total of 184 eyes that were enrolled in miosis, a total of 22 (11.9%) could not be recognized in mydriasis and therefore needed reenrollment. No single case of false-positive acceptance occurred in either group. The results of this trial indicate that standard cataract surgery seems not to be a limiting factor for iris recognition in the large majority of cases. Some patients (5.2% in this study) might need "reenrollment" after cataract surgery. Iris recognition was primarily successful in eyes with medically dilated pupils in nearly 9 out of 10 eyes. No single case of false-positive acceptance occurred in either group in this trial. It seems therefore that iris recognition is a valid biometric method in the majority of cases after cataract surgery or after pupil dilation.

Multi-objective reliability redundancy allocation in an interval environment using particle swarm optimization

International Nuclear Information System (INIS)

Zhang, Enze; Chen, Qingwei

2016-01-01

Most of the existing works addressing reliability redundancy allocation problems are based on the assumption of fixed reliabilities of components. In real-life situations, however, the reliabilities of individual components may be imprecise, most often given as intervals, under different operating or environmental conditions. This paper deals with reliability redundancy allocation problems modeled in an interval environment. An interval multi-objective optimization problem is formulated from the original crisp one, where system reliability and cost are simultaneously considered. To render the multi-objective particle swarm optimization (MOPSO) algorithm capable of dealing with interval multi-objective optimization problems, a dominance relation for interval-valued functions is defined with the help of our newly proposed order relations of interval-valued numbers. Then, the crowding distance is extended to the multi-objective interval-valued case. Finally, the effectiveness of the proposed approach has been demonstrated through two numerical examples and a case study of supervisory control and data acquisition (SCADA) system in water resource management. - Highlights: • We model the reliability redundancy allocation problem in an interval environment. • We apply the particle swarm optimization directly on the interval values. • A dominance relation for interval-valued multi-objective functions is defined. • The crowding distance metric is extended to handle imprecise objective functions.

Distinct roles of the hippocampus and perirhinal cortex in GABAA receptor blockade-induced enhancement of object recognition memory.

Science.gov (United States)

Kim, Jong Min; Kim, Dong Hyun; Lee, Younghwan; Park, Se Jin; Ryu, Jong Hoon

2014-03-13

It is well known that the hippocampus plays a role in spatial and contextual memory, and that spatial information is tightly regulated by the hippocampus. However, it is still highly controversial whether the hippocampus plays a role in object recognition memory. In a pilot study, the administration of bicuculline, a GABAA receptor antagonist, enhanced memory in the passive avoidance task, but not in the novel object recognition task. In the present study, we hypothesized that these different results are related to the characteristics of each task and the different roles of hippocampus and perirhinal cortex. A region-specific drug-treatment model was employed to clarify the role of the hippocampus and perirhinal cortex in object recognition memory. After a single habituation in the novel object recognition task, intra-perirhinal cortical injection of bicuculline increased and intra-hippocampal injection decreased the exploration time ratio to novel object. In addition, when animals were repeatedly habituated to the context, intra-perirhinal cortical administration of bicuculline still increased exploration time ratio to novel object, but the effect of intra-hippocampal administration disappeared. Concurrent increases of c-Fos expression and ERK phosphorylation were observed in the perirhinal cortex of the object with context-exposed group either after single or repeated habituation to the context, but no changes were noted in the hippocampus. Altogether, these results suggest that object recognition memory formation requires the perirhinal cortex but not the hippocampus, and that hippocampal activation interferes with object recognition memory by the information encoding of unfamiliar environment. Copyright © 2014 Elsevier B.V. All rights reserved.

Hippocampal NMDA receptors are involved in rats' spontaneous object recognition only under high memory load condition.

Science.gov (United States)

Sugita, Manami; Yamada, Kazuo; Iguchi, Natsumi; Ichitani, Yukio

2015-10-22

The possible involvement of hippocampal N-methyl-D-aspartate (NMDA) receptors in spontaneous object recognition was investigated in rats under different memory load conditions. We first estimated rats' object memory span using 3-5 objects in "Different Objects Task (DOT)" in order to confirm the highest memory load condition in object recognition memory. Rats were allowed to explore a field in which 3 (3-DOT), 4 (4-DOT), or 5 (5-DOT) different objects were presented. After a delay period, they were placed again in the same field in which one of the sample objects was replaced by another object, and their object exploration behavior was analyzed. Rats could differentiate the novel object from the familiar ones in 3-DOT and 4-DOT but not in 5-DOT, suggesting that rats' object memory span was about 4. Then, we examined the effects of hippocampal AP5 infusion on performance in both 2-DOT (2 different objects were used) and 4-DOT. The drug treatment before the sample phase impaired performance only in 4-DOT. These results suggest that hippocampal NMDA receptors play a critical role in spontaneous object recognition only when the memory load is high. Copyright © 2015 Elsevier B.V. All rights reserved.

Image object recognition based on the Zernike moment and neural networks

Science.gov (United States)

Wan, Jianwei; Wang, Ling; Huang, Fukan; Zhou, Liangzhu

1998-03-01

This paper first give a comprehensive discussion about the concept of artificial neural network its research methods and the relations with information processing. On the basis of such a discussion, we expound the mathematical similarity of artificial neural network and information processing. Then, the paper presents a new method of image recognition based on invariant features and neural network by using image Zernike transform. The method not only has the invariant properties for rotation, shift and scale of image object, but also has good fault tolerance and robustness. Meanwhile, it is also compared with statistical classifier and invariant moments recognition method.

Joint Tensor Feature Analysis For Visual Object Recognition.

Science.gov (United States)

Wong, Wai Keung; Lai, Zhihui; Xu, Yong; Wen, Jiajun; Ho, Chu Po

2015-11-01

Tensor-based object recognition has been widely studied in the past several years. This paper focuses on the issue of joint feature selection from the tensor data and proposes a novel method called joint tensor feature analysis (JTFA) for tensor feature extraction and recognition. In order to obtain a set of jointly sparse projections for tensor feature extraction, we define the modified within-class tensor scatter value and the modified between-class tensor scatter value for regression. The k-mode optimization technique and the L(2,1)-norm jointly sparse regression are combined together to compute the optimal solutions. The convergent analysis, computational complexity analysis and the essence of the proposed method/model are also presented. It is interesting to show that the proposed method is very similar to singular value decomposition on the scatter matrix but with sparsity constraint on the right singular value matrix or eigen-decomposition on the scatter matrix with sparse manner. Experimental results on some tensor datasets indicate that JTFA outperforms some well-known tensor feature extraction and selection algorithms.

Where vision meets memory: prefrontal-posterior networks for visual object constancy during categorization and recognition.

Science.gov (United States)

Schendan, Haline E; Stern, Chantal E

2008-07-01

Objects seen from unusual relative to more canonical views require more time to categorize and recognize, and, according to object model verification theories, additionally recruit prefrontal processes for cognitive control that interact with parietal processes for mental rotation. To test this using functional magnetic resonance imaging, people categorized and recognized known objects from unusual and canonical views. Canonical views activated some components of a default network more on categorization than recognition. Activation to unusual views showed that both ventral and dorsal visual pathways, and prefrontal cortex, have key roles in visual object constancy. Unusual views activated object-sensitive and mental rotation (and not saccade) regions in ventrocaudal intraparietal, transverse occipital, and inferotemporal sulci, and ventral premotor cortex for verification processes of model testing on any task. A collateral-lingual sulci "place" area activated for mental rotation, working memory, and unusual views on correct recognition and categorization trials to accomplish detailed spatial matching. Ventrolateral prefrontal cortex and object-sensitive lateral occipital sulcus activated for mental rotation and unusual views on categorization more than recognition, supporting verification processes of model prediction. This visual knowledge framework integrates vision and memory theories to explain how distinct prefrontal-posterior networks enable meaningful interactions with objects in diverse situations.

Representations and Techniques for 3D Object Recognition and Scene Interpretation

CERN Document Server

Hoiem, Derek

2011-01-01

One of the grand challenges of artificial intelligence is to enable computers to interpret 3D scenes and objects from imagery. This book organizes and introduces major concepts in 3D scene and object representation and inference from still images, with a focus on recent efforts to fuse models of geometry and perspective with statistical machine learning. The book is organized into three sections: (1) Interpretation of Physical Space; (2) Recognition of 3D Objects; and (3) Integrated 3D Scene Interpretation. The first discusses representations of spatial layout and techniques to interpret physi

Deformation-specific and deformation-invariant visual object recognition: pose vs identity recognition of people and deforming objects

Directory of Open Access Journals (Sweden)

Tristan J Webb

2014-04-01

Full Text Available When we see a human sitting down, standing up, or walking, we can recognise one of these poses independently of the individual, or we can recognise the individual person, independently of the pose. The same issues arise for deforming objects. For example, if we see a flag deformed by the wind, either blowing out or hanging languidly, we can usually recognise the flag, independently of its deformation; or we can recognise the deformation independently of the identity of the flag. We hypothesize that these types of recognition can be implemented by the primate visual system using temporo-spatial continuity as objects transform as a learning principle. In particular, we hypothesize that pose or deformation can be learned under conditions in which large numbers of different people are successively seen in the same pose, or objects in the same deformation. We also hypothesize that person-specific representations that are independent of pose, and object-specific representations that are independent of deformation and view, could be built, when individual people or objects are observed successively transforming from one pose or deformation and view to another. These hypotheses were tested in a simulation of the ventral visual system, VisNet, that uses temporal continuity, implemented in a synaptic learning rule with a short-term memory trace of previous neuronal activity, to learn invariant representations. It was found that depending on the statistics of the visual input, either pose-specific or deformation-specific representations could be built that were invariant with respect to individual and view; or that identity-specific representations could be built that were invariant with respect to pose or deformation and view. We propose that this is how pose-specific and pose-invariant, and deformation-specific and deformation-invariant, perceptual representations are built in the brain.

Are Face and Object Recognition Independent? A Neurocomputational Modeling Exploration.

Science.gov (United States)

Wang, Panqu; Gauthier, Isabel; Cottrell, Garrison

2016-04-01

Are face and object recognition abilities independent? Although it is commonly believed that they are, Gauthier et al. [Gauthier, I., McGugin, R. W., Richler, J. J., Herzmann, G., Speegle, M., & VanGulick, A. E. Experience moderates overlap between object and face recognition, suggesting a common ability. Journal of Vision, 14, 7, 2014] recently showed that these abilities become more correlated as experience with nonface categories increases. They argued that there is a single underlying visual ability, v, that is expressed in performance with both face and nonface categories as experience grows. Using the Cambridge Face Memory Test and the Vanderbilt Expertise Test, they showed that the shared variance between Cambridge Face Memory Test and Vanderbilt Expertise Test performance increases monotonically as experience increases. Here, we address why a shared resource across different visual domains does not lead to competition and to an inverse correlation in abilities? We explain this conundrum using our neurocomputational model of face and object processing ["The Model", TM, Cottrell, G. W., & Hsiao, J. H. Neurocomputational models of face processing. In A. J. Calder, G. Rhodes, M. Johnson, & J. Haxby (Eds.), The Oxford handbook of face perception. Oxford, UK: Oxford University Press, 2011]. We model the domain general ability v as the available computational resources (number of hidden units) in the mapping from input to label and experience as the frequency of individual exemplars in an object category appearing during network training. Our results show that, as in the behavioral data, the correlation between subordinate level face and object recognition accuracy increases as experience grows. We suggest that different domains do not compete for resources because the relevant features are shared between faces and objects. The essential power of experience is to generate a "spreading transform" for faces (separating them in representational space) that

[Recognition of visual objects under forward masking. Effects of cathegorial similarity of test and masking stimuli].

Science.gov (United States)

Gerasimenko, N Iu; Slavutskaia, A V; Kalinin, S A; Kulikov, M A; Mikhaĭlova, E S

2013-01-01

In 38 healthy subjects accuracy and response time were examined during recognition of two categories of images--animals andnonliving objects--under forward masking. We revealed new data that masking effects depended of categorical similarity of target and masking stimuli. The recognition accuracy was the lowest and the response time was the most slow, when the target and masking stimuli belongs to the same category, that was combined with high dispersion of response times. The revealed effects were more clear in the task of animal recognition in comparison with the recognition of nonliving objects. We supposed that the revealed effects connected with interference between cortical representations of the target and masking stimuli and discussed our results in context of cortical interference and negative priming.

Higher-order neural network software for distortion invariant object recognition

Science.gov (United States)

Reid, Max B.; Spirkovska, Lilly

1991-01-01

The state-of-the-art in pattern recognition for such applications as automatic target recognition and industrial robotic vision relies on digital image processing. We present a higher-order neural network model and software which performs the complete feature extraction-pattern classification paradigm required for automatic pattern recognition. Using a third-order neural network, we demonstrate complete, 100 percent accurate invariance to distortions of scale, position, and in-plate rotation. In a higher-order neural network, feature extraction is built into the network, and does not have to be learned. Only the relatively simple classification step must be learned. This is key to achieving very rapid training. The training set is much smaller than with standard neural network software because the higher-order network only has to be shown one view of each object to be learned, not every possible view. The software and graphical user interface run on any Sun workstation. Results of the use of the neural software in autonomous robotic vision systems are presented. Such a system could have extensive application in robotic manufacturing.

Reliability-oriented multi-objective optimal decision-making approach for uncertainty-based watershed load reduction

International Nuclear Information System (INIS)

Dong, Feifei; Liu, Yong; Su, Han; Zou, Rui; Guo, Huaicheng

2015-01-01

Water quality management and load reduction are subject to inherent uncertainties in watershed systems and competing decision objectives. Therefore, optimal decision-making modeling in watershed load reduction is suffering due to the following challenges: (a) it is difficult to obtain absolutely “optimal” solutions, and (b) decision schemes may be vulnerable to failure. The probability that solutions are feasible under uncertainties is defined as reliability. A reliability-oriented multi-objective (ROMO) decision-making approach was proposed in this study for optimal decision making with stochastic parameters and multiple decision reliability objectives. Lake Dianchi, one of the three most eutrophic lakes in China, was examined as a case study for optimal watershed nutrient load reduction to restore lake water quality. This study aimed to maximize reliability levels from considerations of cost and load reductions. The Pareto solutions of the ROMO optimization model were generated with the multi-objective evolutionary algorithm, demonstrating schemes representing different biases towards reliability. The Pareto fronts of six maximum allowable emission (MAE) scenarios were obtained, which indicated that decisions may be unreliable under unpractical load reduction requirements. A decision scheme identification process was conducted using the back propagation neural network (BPNN) method to provide a shortcut for identifying schemes at specific reliability levels for decision makers. The model results indicated that the ROMO approach can offer decision makers great insights into reliability tradeoffs and can thus help them to avoid ineffective decisions. - Highlights: • Reliability-oriented multi-objective (ROMO) optimal decision approach was proposed. • The approach can avoid specifying reliability levels prior to optimization modeling. • Multiple reliability objectives can be systematically balanced using Pareto fronts. • Neural network model was used to

Reliability-oriented multi-objective optimal decision-making approach for uncertainty-based watershed load reduction

Energy Technology Data Exchange (ETDEWEB)

Dong, Feifei [College of Environmental Science and Engineering, Key Laboratory of Water and Sediment Sciences (MOE), Peking University, Beijing 100871 (China); Liu, Yong, E-mail: yongliu@pku.edu.cn [College of Environmental Science and Engineering, Key Laboratory of Water and Sediment Sciences (MOE), Peking University, Beijing 100871 (China); Institute of Water Sciences, Peking University, Beijing 100871 (China); Su, Han [College of Environmental Science and Engineering, Key Laboratory of Water and Sediment Sciences (MOE), Peking University, Beijing 100871 (China); Zou, Rui [Tetra Tech, Inc., 10306 Eaton Place, Ste 340, Fairfax, VA 22030 (United States); Yunnan Key Laboratory of Pollution Process and Management of Plateau Lake-Watershed, Kunming 650034 (China); Guo, Huaicheng [College of Environmental Science and Engineering, Key Laboratory of Water and Sediment Sciences (MOE), Peking University, Beijing 100871 (China)

2015-05-15

Water quality management and load reduction are subject to inherent uncertainties in watershed systems and competing decision objectives. Therefore, optimal decision-making modeling in watershed load reduction is suffering due to the following challenges: (a) it is difficult to obtain absolutely “optimal” solutions, and (b) decision schemes may be vulnerable to failure. The probability that solutions are feasible under uncertainties is defined as reliability. A reliability-oriented multi-objective (ROMO) decision-making approach was proposed in this study for optimal decision making with stochastic parameters and multiple decision reliability objectives. Lake Dianchi, one of the three most eutrophic lakes in China, was examined as a case study for optimal watershed nutrient load reduction to restore lake water quality. This study aimed to maximize reliability levels from considerations of cost and load reductions. The Pareto solutions of the ROMO optimization model were generated with the multi-objective evolutionary algorithm, demonstrating schemes representing different biases towards reliability. The Pareto fronts of six maximum allowable emission (MAE) scenarios were obtained, which indicated that decisions may be unreliable under unpractical load reduction requirements. A decision scheme identification process was conducted using the back propagation neural network (BPNN) method to provide a shortcut for identifying schemes at specific reliability levels for decision makers. The model results indicated that the ROMO approach can offer decision makers great insights into reliability tradeoffs and can thus help them to avoid ineffective decisions. - Highlights: • Reliability-oriented multi-objective (ROMO) optimal decision approach was proposed. • The approach can avoid specifying reliability levels prior to optimization modeling. • Multiple reliability objectives can be systematically balanced using Pareto fronts. • Neural network model was used to

Dopamine D1 receptor stimulation modulates the formation and retrieval of novel object recognition memory: Role of the prelimbic cortex.

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Pezze, Marie A; Marshall, Hayley J; Fone, Kevin C F; Cassaday, Helen J

2015-11-01

Previous studies have shown that dopamine D1 receptor antagonists impair novel object recognition memory but the effects of dopamine D1 receptor stimulation remain to be determined. This study investigated the effects of the selective dopamine D1 receptor agonist SKF81297 on acquisition and retrieval in the novel object recognition task in male Wistar rats. SKF81297 (0.4 and 0.8 mg/kg s.c.) given 15 min before the sampling phase impaired novel object recognition evaluated 10 min or 24 h later. The same treatments also reduced novel object recognition memory tested 24 h after the sampling phase and when given 15 min before the choice session. These data indicate that D1 receptor stimulation modulates both the encoding and retrieval of object recognition memory. Microinfusion of SKF81297 (0.025 or 0.05 μg/side) into the prelimbic sub-region of the medial prefrontal cortex (mPFC) in this case 10 min before the sampling phase also impaired novel object recognition memory, suggesting that the mPFC is one important site mediating the effects of D1 receptor stimulation on visual recognition memory. Copyright © 2015 The Authors. Published by Elsevier B.V. All rights reserved.

Field of attention for instantaneous object recognition.

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Jian-Gao Yao

Full Text Available BACKGROUND: Instantaneous object discrimination and categorization are fundamental cognitive capacities performed with the guidance of visual attention. Visual attention enables selection of a salient object within a limited area of the visual field; we referred to as "field of attention" (FA. Though there is some evidence concerning the spatial extent of object recognition, the following questions still remain unknown: (a how large is the FA for rapid object categorization, (b how accuracy of attention is distributed over the FA, and (c how fast complex objects can be categorized when presented against backgrounds formed by natural scenes. METHODOLOGY/PRINCIPAL FINDINGS: To answer these questions, we used a visual perceptual task in which subjects were asked to focus their attention on a point while being required to categorize briefly flashed (20 ms photographs of natural scenes by indicating whether or not these contained an animal. By measuring the accuracy of categorization at different eccentricities from the fixation point, we were able to determine the spatial extent and the distribution of accuracy over the FA, as well as the speed of categorizing objects using stimulus onset asynchrony (SOA. Our results revealed that subjects are able to rapidly categorize complex natural images within about 0.1 s without eye movement, and showed that the FA for instantaneous image categorization covers a visual field extending 20° × 24°, and accuracy was highest (>90% at the center of FA and declined with increasing eccentricity. CONCLUSIONS/SIGNIFICANCE: In conclusion, human beings are able to categorize complex natural images at a glance over a large extent of the visual field without eye movement.

Effects of Acute Administration of Urtica dioica on the Novel Object-Recognition Task in Mice

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Hashemi-Firouzi

2015-08-01

Full Text Available Background Urtica dioica (nettle has a variety of uses in traditional medicine for the treatment of certain urogenital problems, gastrointestinal disorders, and diabetes. Objectives Recent studies have implicated the effect of U. dioica on brain functions such as pain and memory. However, there is no direct evidence of the acute effects of this plant on cognition. The aim of the present study was to evaluate the effect of U. dioica aqueous extract on the novel object-recognition task (NOR in mice. Materials and Methods First, U. dioica aqueous extract was prepared, then adult male mice were randomly divided into four experimental groups. During the training session, the mice were placed in a box and given 5 minutes to explore two identical objects. The next day, they were again placed in the box and allowed to explore one familiar and one novel object. They received intraperitoneal injections of saline or U. dioica aqueous extract (100 mg/kg before or immediately after the training session or before the test session of the NOR task. Results The results showed that there was a preference for the novel object compared to the familiar one in each of the experimental groups. The object-recognition discrimination index in the group of mice that received U. dioica before training was significantly less than in the other experimental groups. There was no significant difference in the discrimination index between the other groups. U. dioica did not decrease the time spent exploring familiar and unfamiliar objects, or the total time spent exploring both objects. Conclusions Acute administration of U. dioica impairs the object-recognition task if it is used only before the training session. This may be due to its modulation on the acquisition processing of object-recognition. U. dioica has no significant effects on the consolidation or retrieval processing stages of the NOR task. These results emphasize the unfavorable effect on cognitive function of pre

Involvement of hippocampal NMDA receptors in retrieval of spontaneous object recognition memory in rats.

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Iwamura, Etsushi; Yamada, Kazuo; Ichitani, Yukio

2016-07-01

The involvement of hippocampal N-methyl-d-aspartate (NMDA) receptors in the retrieval process of spontaneous object recognition memory was investigated. The spontaneous object recognition test consisted of three phases. In the sample phase, rats were exposed to two identical objects several (2-5) times in the arena. After the sample phase, various lengths of delay intervals (24h-6 weeks) were inserted (delay phase). In the test phase in which both the familiar and the novel objects were placed in the arena, rats' novel object exploration behavior under the hippocampal treatment of NMDA receptor antagonist, AP5, or vehicle was observed. With 5 exposure sessions in the sample phase (experiment 1), AP5 treatment in the test phase significantly decreased discrimination ratio when the delay was 3 weeks but not when it was one week. On the other hand, with 2 exposure sessions in the sample phase (experiment 2) in which even vehicle-injected control animals could not discriminate the novel object from the familiar one with a 3 week delay, AP5 treatment significantly decreased discrimination ratio when the delay was one week, but not when it was 24h. Additional experiment (experiment 3) showed that the hippocampal treatment of an α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) receptor antagonist, NBQX, decreased discrimination ratio with all delay intervals tested (24h-3 weeks). Results suggest that hippocampal NMDA receptors play an important role in the retrieval of spontaneous object recognition memory especially when the memory trace weakens. Copyright © 2016. Published by Elsevier B.V.

3-D OBJECT RECOGNITION FROM POINT CLOUD DATA

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W. Smith

2012-09-01

Full Text Available The market for real-time 3-D mapping includes not only traditional geospatial applications but also navigation of unmanned autonomous vehicles (UAVs. Massively parallel processes such as graphics processing unit (GPU computing make real-time 3-D object recognition and mapping achievable. Geospatial technologies such as digital photogrammetry and GIS offer advanced capabilities to produce 2-D and 3-D static maps using UAV data. The goal is to develop real-time UAV navigation through increased automation. It is challenging for a computer to identify a 3-D object such as a car, a tree or a house, yet automatic 3-D object recognition is essential to increasing the productivity of geospatial data such as 3-D city site models. In the past three decades, researchers have used radiometric properties to identify objects in digital imagery with limited success, because these properties vary considerably from image to image. Consequently, our team has developed software that recognizes certain types of 3-D objects within 3-D point clouds. Although our software is developed for modeling, simulation and visualization, it has the potential to be valuable in robotics and UAV applications. The locations and shapes of 3-D objects such as buildings and trees are easily recognizable by a human from a brief glance at a representation of a point cloud such as terrain-shaded relief. The algorithms to extract these objects have been developed and require only the point cloud and minimal human inputs such as a set of limits on building size and a request to turn on a squaring option. The algorithms use both digital surface model (DSM and digital elevation model (DEM, so software has also been developed to derive the latter from the former. The process continues through the following steps: identify and group 3-D object points into regions; separate buildings and houses from trees; trace region boundaries; regularize and simplify boundary polygons; construct complex

3-D Object Recognition from Point Cloud Data

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Smith, W.; Walker, A. S.; Zhang, B.

2011-09-01

The market for real-time 3-D mapping includes not only traditional geospatial applications but also navigation of unmanned autonomous vehicles (UAVs). Massively parallel processes such as graphics processing unit (GPU) computing make real-time 3-D object recognition and mapping achievable. Geospatial technologies such as digital photogrammetry and GIS offer advanced capabilities to produce 2-D and 3-D static maps using UAV data. The goal is to develop real-time UAV navigation through increased automation. It is challenging for a computer to identify a 3-D object such as a car, a tree or a house, yet automatic 3-D object recognition is essential to increasing the productivity of geospatial data such as 3-D city site models. In the past three decades, researchers have used radiometric properties to identify objects in digital imagery with limited success, because these properties vary considerably from image to image. Consequently, our team has developed software that recognizes certain types of 3-D objects within 3-D point clouds. Although our software is developed for modeling, simulation and visualization, it has the potential to be valuable in robotics and UAV applications. The locations and shapes of 3-D objects such as buildings and trees are easily recognizable by a human from a brief glance at a representation of a point cloud such as terrain-shaded relief. The algorithms to extract these objects have been developed and require only the point cloud and minimal human inputs such as a set of limits on building size and a request to turn on a squaring option. The algorithms use both digital surface model (DSM) and digital elevation model (DEM), so software has also been developed to derive the latter from the former. The process continues through the following steps: identify and group 3-D object points into regions; separate buildings and houses from trees; trace region boundaries; regularize and simplify boundary polygons; construct complex roofs. Several case

One-trial object recognition memory in the domestic rabbit (Oryctolagus cuniculus) is disrupted by NMDA receptor antagonists.

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Hoffman, Kurt Leroy; Basurto, Enrique

2013-08-01

The spontaneous response to novelty is the basis of one-trial object recognition tests for the study of object recognition memory (ORM) in rodents. We describe an object recognition task for the rabbit, based on its natural tendency to scent-mark ("chin") novel objects. The object recognition task comprised a 15min sample phase in which the rabbit was placed into an open field arena containing two similar objects, then removed for a 5-360min delay, and then returned to the same arena that contained one object similar to the original ones ("Familiar") and one that differed from the original ones ("Novel"), for a 15min test phase. Chin-marks directed at each of the objects were registered. Some animals received injections (sc) of saline, ketamine (1mg/kg), or MK-801 (37μg/kg), 5 or 20min before the sample phase. We found that chinning decreased across the sample phase, and that this response showed stimulus specificity, a defining characteristic of habituation: in the test phase, chinning directed at the Novel, but not Familiar, object was increased. Chinning directed preferentially at the novel object, which we interpret as novelty-induced sensitization and the behavioral correlate of ORM, was promoted by tactile/visual and spatial novelty. ORM deficits were induced by pre-treatment with MK-801 and, to a lesser extent, ketamine. Novel object discrimination was not observed after delays longer than 5min. These results suggest that short-term habituation and sensitization, not long-term memory, underlie novel object discrimination in this test paradigm. Copyright © 2013 Elsevier B.V. All rights reserved.

Short-term plasticity of visuo-haptic object recognition

DEFF Research Database (Denmark)

Kassuba, Tanja; Klinge, Corinna; Hölig, Cordula

2014-01-01

, the same stimulation gave rise to relative increases in activation during S2 processing in the right LO, left FG, bilateral IPS, and other regions previously associated with object recognition. Critically, the modality of S2 determined which regions were recruited after rTMS. Relative to sham rTMS, real r......TMS induced increased activations during crossmodal congruent matching in the left FG for haptic S2 and the temporal pole for visual S2. In addition, we found stronger activations for incongruent than congruent matching in the right anterior parahippocampus and middle frontal gyrus for crossmodal matching......Functional magnetic resonance imaging (fMRI) studies have provided ample evidence for the involvement of the lateral occipital cortex (LO), fusiform gyrus (FG), and intraparietal sulcus (IPS) in visuo-haptic object integration. Here we applied 30 min of sham (non-effective) or real offline 1 Hz...

Fast and efficient indexing approach for object recognition

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Hefnawy, Alaa; Mashali, Samia A.; Rashwan, Mohsen; Fikri, Magdi

1999-08-01

This paper introduces a fast and efficient indexing approach for both 2D and 3D model-based object recognition in the presence of rotation, translation, and scale variations of objects. The indexing entries are computed after preprocessing the data by Haar wavelet decomposition. The scheme is based on a unified image feature detection approach based on Zernike moments. A set of low level features, e.g. high precision edges, gray level corners, are estimated by a set of orthogonal Zernike moments, calculated locally around every image point. A high dimensional, highly descriptive indexing entries are then calculated based on the correlation of these local features and employed for fast access to the model database to generate hypotheses. A list of the most candidate models is then presented by evaluating the hypotheses. Experimental results are included to demonstrate the effectiveness of the proposed indexing approach.

The Role of Sensory-Motor Information in Object Recognition: Evidence from Category-Specific Visual Agnosia

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Wolk, D.A.; Coslett, H.B.; Glosser, G.

2005-01-01

The role of sensory-motor representations in object recognition was investigated in experiments involving AD, a patient with mild visual agnosia who was impaired in the recognition of visually presented living as compared to non-living entities. AD named visually presented items for which sensory-motor information was available significantly more…

Vision holds a greater share in visuo-haptic object recognition than touch

DEFF Research Database (Denmark)

Kassuba, Tanja; Klinge, Corinna; Hölig, Cordula

2013-01-01

approach of multisensory integration would predict that haptics as the less efficient sense for object recognition gains more from integrating additional visual information than vice versa. To test for asymmetries between vision and touch in visuo-haptic interactions, we measured regional changes in brain...... processed the target object, being more pronounced for haptic than visual targets. This preferential response of visuo-haptic regions indicates a modality-specific asymmetry in crossmodal matching of visual and haptic object features, suggesting a functional primacy of vision over touch in visuo...

Nicotine enhances the reconsolidation of novel object recognition memory in rats.

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Tian, Shaowen; Pan, Si; You, Yong

2015-02-01

There is increasing evidence that nicotine is involved in learning and memory. However, there are only few studies that have evaluated the relationship between nicotine and memory reconsolidation. In this study, we investigated the effects of nicotine on the reconsolidation of novel object recognition memory in rats. Behavior procedure involved four training phases: habituation (Days 1 and 2), sample (Day 3), reactivation (Day 4) and test (Day 6). Rats were injected with saline or nicotine (0.1, 0.2 and 0.4 mg/kg) immediately or 6h after reactivation. The discrimination index was used to assess memory performance and calculated as the difference in time exploring on the novel and familiar objects. Results showed that nicotine administration immediately but not 6 h after reactivation significantly enhanced memory performance of rats. Further results showed that the enhancing effect of nicotine on memory performance was dependent on memory reactivation, and was not attributed to the changes of the nonspecific responses (locomotor activity and anxiety level) 48 h after nicotine administration. The results suggest that post-reactivation nicotine administration enhances the reconsolidation of novel object recognition memory. Our present finding extends previous research on the nicotinic effects on learning and memory. Copyright © 2014 Elsevier Inc. All rights reserved.

Specific and Class Object Recognition for Service Robots through Autonomous and Interactive Methods

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Mansur, Al; Kuno, Yoshinori

Service robots need to be able to recognize and identify objects located within complex backgrounds. Since no single method may work in every situation, several methods need to be combined and robots have to select the appropriate one automatically. In this paper we propose a scheme to classify situations depending on the characteristics of the object of interest and user demand. We classify situations into four groups and employ different techniques for each. We use Scale-invariant feature transform (SIFT), Kernel Principal Components Analysis (KPCA) in conjunction with Support Vector Machine (SVM) using intensity, color, and Gabor features for five object categories. We show that the use of appropriate features is important for the use of KPCA and SVM based techniques on different kinds of objects. Through experiments we show that by using our categorization scheme a service robot can select an appropriate feature and method, and considerably improve its recognition performance. Yet, recognition is not perfect. Thus, we propose to combine the autonomous method with an interactive method that allows the robot to recognize the user request for a specific object and class when the robot fails to recognize the object. We also propose an interactive way to update the object model that is used to recognize an object upon failure in conjunction with the user's feedback.

System safety and reliability using object-oriented programming techniques

International Nuclear Information System (INIS)

Patterson-Hine, F.A.; Koen, B.V.

1987-01-01

Direct evaluation fault tree codes have been written in recursive, list-processing computer languages such as PL/1 (PATREC-I) and LISP (PATREC-L). The pattern-matching strategy implemented in these codes has been used extensively in France to evaluate system reliability. Recent reviews of the risk management process suggest that a data base containing plant-specific information be integrated with a package of codes used for probabilistic risk assessment (PRA) to alleviate some of the difficulties that make a PRA so costly and time-intensive. A new programming paradigm, object-oriented programming, is uniquely suited for the development of such a software system. A knowledge base and fault tree evaluation algorithm, based on previous experience with PATREC-L, have been implemented using object-oriented techniques, resulting in a reliability assessment environment that is easy to develop, modify, and extend

Rapid eye movement sleep deprivation disrupts consolidation but not reconsolidation of novel object recognition memory in rats.

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Chen, Lin; Tian, Shaowen; Ke, Jie

2014-03-20

There is increasing evidence that sleep plays a critical role in memory consolidation. However, there are comparatively few studies that have assessed the relationship between sleep and memory reconsolidation. In the present study, we explored the effects of rapid eye movement sleep deprivation (RSD) on the consolidation (experiment 1) and reconsolidation (experiment 2) of novel object recognition memory in rats. In experiment 1 behavioral procedure involved two training phases: sample and test. Rats were subjected to 6h RSD starting either immediately after sample (exposed to 2 objects) or 6h later. In experiment 2 behavioral procedure involved three training phases: sample, reactivation and test. Rats were subjected to 6h RSD starting either immediately after reactivation (exposed to the same 2 sample objects to reactivate the memory trace) or 6h later. Results from experiment 1 showed that post-sample RSD from 0 to 6h but not 6 to 12h disrupted novel object recognition memory consolidation. However, we found that post-reactivation RSD whether from 0 to 6h or 6 to 12h had no effect on novel object recognition memory reconsolidation in experiment 2. The results indicated that RSD selectively disrupted consolidation of novel object recognition memory, suggesting a dissociation effect of RSD on consolidation and reconsolidation. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Why does brain damage impair memory? A connectionist model of object recognition memory in perirhinal cortex.

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Cowell, Rosemary A; Bussey, Timothy J; Saksida, Lisa M

2006-11-22

Object recognition is the canonical test of declarative memory, the type of memory putatively impaired after damage to the temporal lobes. Studies of object recognition memory have helped elucidate the anatomical structures involved in declarative memory, indicating a critical role for perirhinal cortex. We offer a mechanistic account of the effects of perirhinal cortex damage on object recognition memory, based on the assumption that perirhinal cortex stores representations of the conjunctions of visual features possessed by complex objects. Such representations are proposed to play an important role in memory when it is difficult to solve a task using representations of only individual visual features of stimuli, thought to be stored in regions of the ventral visual stream caudal to perirhinal cortex. The account is instantiated in a connectionist model, in which development of object representations with visual experience provides a mechanism for judgment of previous occurrence. We present simulations addressing the following empirical findings: (1) that impairments after damage to perirhinal cortex (modeled by removing the "perirhinal cortex" layer of the network) are exacerbated by lengthening the delay between presentation of to-be-remembered items and test, (2) that such impairments are also exacerbated by lengthening the list of to-be-remembered items, and (3) that impairments are revealed only when stimuli are trial unique rather than repeatedly presented. This study shows that it may be possible to account for object recognition impairments after damage to perirhinal cortex within a hierarchical, representational framework, in which complex conjunctive representations in perirhinal cortex play a critical role.

Knowledge-based object recognition for different morphological classes of plants

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Brendel, Thorsten; Schwanke, Joerg; Jensch, Peter F.; Megnet, Roland

1995-01-01

Micropropagation of plants is done by cutting juvenile plants and placing them into special container-boxes with nutrient-solution where the pieces can grow up and be cut again several times. To produce high amounts of biomass it is necessary to do plant micropropagation by a robotic syshoot. In this paper we describe parts of the vision syshoot that recognizes plants and their particular cutting points. Therefore, it is necessary to extract elements of the plants and relations between these elements (for example root, shoot, leaf). Different species vary in their morphological appearance, variation is also immanent in plants of the same species. Therefore, we introduce several morphological classes of plants from that we expect same recognition methods. As a result of our work we present rules which help users to create specific algorithms for object recognition of plant species.

Face Memory and Object Recognition in Children with High-Functioning Autism or Asperger Syndrome and in Their Parents

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Kuusikko-Gauffin, Sanna; Jansson-Verkasalo, Eira; Carter, Alice; Pollock-Wurman, Rachel; Jussila, Katja; Mattila, Marja-Leena; Rahko, Jukka; Ebeling, Hanna; Pauls, David; Moilanen, Irma

2011-01-01

Children with Autism Spectrum Disorders (ASDs) have reported to have impairments in face, recognition and face memory, but intact object recognition and object memory. Potential abnormalities, in these fields at the family level of high-functioning children with ASD remains understudied despite, the ever-mounting evidence that ASDs are genetic and…

Deep neural networks rival the representation of primate IT cortex for core visual object recognition.

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Charles F Cadieu

2014-12-01

Full Text Available The primate visual system achieves remarkable visual object recognition performance even in brief presentations, and under changes to object exemplar, geometric transformations, and background variation (a.k.a. core visual object recognition. This remarkable performance is mediated by the representation formed in inferior temporal (IT cortex. In parallel, recent advances in machine learning have led to ever higher performing models of object recognition using artificial deep neural networks (DNNs. It remains unclear, however, whether the representational performance of DNNs rivals that of the brain. To accurately produce such a comparison, a major difficulty has been a unifying metric that accounts for experimental limitations, such as the amount of noise, the number of neural recording sites, and the number of trials, and computational limitations, such as the complexity of the decoding classifier and the number of classifier training examples. In this work, we perform a direct comparison that corrects for these experimental limitations and computational considerations. As part of our methodology, we propose an extension of "kernel analysis" that measures the generalization accuracy as a function of representational complexity. Our evaluations show that, unlike previous bio-inspired models, the latest DNNs rival the representational performance of IT cortex on this visual object recognition task. Furthermore, we show that models that perform well on measures of representational performance also perform well on measures of representational similarity to IT, and on measures of predicting individual IT multi-unit responses. Whether these DNNs rely on computational mechanisms similar to the primate visual system is yet to be determined, but, unlike all previous bio-inspired models, that possibility cannot be ruled out merely on representational performance grounds.

Differential cortical c-Fos and Zif-268 expression after object and spatial memory processing in a standard or episodic-like object recognition task

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Flávio F Barbosa

2013-08-01

Full Text Available Episodic memory reflects the capacity to recollect what, where and when a specific event happened in an integrative manner. Animal studies have suggested that the medial temporal lobe and the medial pre-frontal cortex are important for episodic-like memory formation. The goal of present study was to evaluate whether there are different patterns of expression of the immediate early genes c-Fos and Zif-268 in these cortical areas after rats are exposed to object recognition tasks with different cognitive demands. Male rats were randomly assigned to five groups: home cage control (CTR-HC, empty open field (CTR-OF, open field with one object (CTR-OF + Obj, novel object recognition task (OR and episodic-like memory task (ELM and were killed one hour after the last behavioral procedure. Rats were able to discriminate the objects in the OR task. In the ELM task, rats showed spatial (but not temporal discrimination of the objects. We found an increase in the c-Fos expression in the dorsal dentate gyrus (DG and in the perirhinal cortex (PRh in the OR and ELM groups. The OR group also presented an increase of c-Fos expression in the medial prefrontal cortex (mPFC. Additionally, the OR and ELM groups had increased expression of Zif-268 in the mPFC. Moreover, Zif-268 was increased in the dorsal CA1 and perirhinal cortex only in the ELM group. In conclusion, the pattern of activation was different in tasks with different cognitive demands. Accordingly, correlation tests suggest the engagement of different neural networks in the object recognition tasks used. Specifically, perirhinal-dentate gyrus co-activation was detected after the what-where memory retrieval, but not after the novel object recognition task. Both regions correlated with the respective behavioral outcome. These findings can be helpful in the understanding of the neural networks underlying memory tasks with different cognitive demands.

Mice deficient for striatal Vesicular Acetylcholine Transporter (VAChT) display impaired short-term but normal long-term object recognition memory.

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Palmer, Daniel; Creighton, Samantha; Prado, Vania F; Prado, Marco A M; Choleris, Elena; Winters, Boyer D

2016-09-15

Substantial evidence implicates Acetylcholine (ACh) in the acquisition of object memories. While most research has focused on the role of the cholinergic basal forebrain and its cortical targets, there are additional cholinergic networks that may contribute to object recognition. The striatum contains an independent cholinergic network comprised of interneurons. In the current study, we investigated the role of this cholinergic signalling in object recognition using mice deficient for Vesicular Acetylcholine Transporter (VAChT) within interneurons of the striatum. We tested whether these striatal VAChT(D2-Cre-flox/flox) mice would display normal short-term (5 or 15min retention delay) and long-term (3h retention delay) object recognition memory. In a home cage object recognition task, male and female VAChT(D2-Cre-flox/flox) mice were impaired selectively with a 15min retention delay. When tested on an object location task, VAChT(D2-Cre-flox/flox) mice displayed intact spatial memory. Finally, when object recognition was tested in a Y-shaped apparatus, designed to minimize the influence of spatial and contextual cues, only females displayed impaired recognition with a 5min retention delay, but when males were challenged with a 15min retention delay, they were also impaired; neither males nor females were impaired with the 3h delay. The pattern of results suggests that striatal cholinergic transmission plays a role in the short-term memory for object features, but not spatial location. Copyright © 2016 Elsevier B.V. All rights reserved.

The Role of Fixation and Visual Attention in Object Recognition.

Science.gov (United States)

1995-01-01

computers", Technical Report, Aritificial Intelligence Lab, M.I. T., AI-Memo-915, June 1986. [29] D.P. Huttenlocher and S.Ullman, "Object Recognition Using...attention", Technical Report, Aritificial Intelligence Lab, M.I. T., AI-memo-770, Jan 1984. [35] E.Krotkov, K. Henriksen and R. Kories, "Stereo...MIT Artificial Intelligence Laboratory [ PCTBTBimON STATEMENT X \\ Afipioved tor puciic reieo*«* \\ »?*•;.., jDi*tiibutK» U»lisut»d* 19951004

Neurology objective structured clinical examination reliability using generalizability theory.

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Blood, Angela D; Park, Yoon Soo; Lukas, Rimas V; Brorson, James R

2015-11-03

This study examines factors affecting reliability, or consistency of assessment scores, from an objective structured clinical examination (OSCE) in neurology through generalizability theory (G theory). Data include assessments from a multistation OSCE taken by 194 medical students at the completion of a neurology clerkship. Facets evaluated in this study include cases, domains, and items. Domains refer to areas of skill (or constructs) that the OSCE measures. G theory is used to estimate variance components associated with each facet, derive reliability, and project the number of cases required to obtain a reliable (consistent, precise) score. Reliability using G theory is moderate (Φ coefficient = 0.61, G coefficient = 0.64). Performance is similar across cases but differs by the particular domain, such that the majority of variance is attributed to the domain. Projections in reliability estimates reveal that students need to participate in 3 OSCE cases in order to increase reliability beyond the 0.70 threshold. This novel use of G theory in evaluating an OSCE in neurology provides meaningful measurement characteristics of the assessment. Differing from prior work in other medical specialties, the cases students were randomly assigned did not influence their OSCE score; rather, scores varied in expected fashion by domain assessed. © 2015 American Academy of Neurology.

Effects of physical exercise on object recognition memory in adult rats of postnatal isoflurane exposures

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Xiao-yan FANG

2017-08-01

Full Text Available Objective To investigate effects of physical exercise (PE on object recognition memory in adult rats of postnatal isoflurane (Iso exposures. Methods One hundred and ten postnatal 7-day SD rats (P7 were randomly divided into four groups: normal control group (Naive, Naive+PE group (received physical exercise in P21: a treadmill exercise 30min each day, 5 times/week, for 6 weeks, Iso group (three times of 2-hour Iso exposure in P7, P9, and P11, and Iso+PE group (received PE in P21 after postnatal Iso exposures. In P67, behavioral testing was conducted including open field and object recognition task (ORT, recording the time (Discrimination Ratios, DR that rats spent on exploring each object, evaluating effects of PE on object recognition memory. Results There was no significant difference in influence of PE on open field testing in all of the groups (P>0.05. Compared with Naive, there was no group difference in DR (P>0.05 for all groups, but the DR of Iso male rats was significantly higher than that of Naive female rats in P67, with significant difference (P=0.034. Compared with non-PE groups, whether or not postnatal Iso exposures, the DR of PE male groups was significantly higher (compared with Naive and Iso group: P67, P=0.050, P=0.017; P95, P=0.037, P=0.019; in female rats, the DR for ISO+PE group was lower than that of Iso group in P67 (P=0.036, but the DR of Naive+PE group was higher than that of Naive group in P95 (P=0.004. Compared with male rats, the DR of non-PE female rats was significantly higher in P67 (vis. Naive and Iso group: P=0.022, P=0.011; but in P95, the DR of non- Iso female groups was significantly higher than that of male groups (vis. Naive and Naive+PE: P=0.008, P=0.017. Conclusions There is no obvious impact of postnatal Iso exposures on object recognition memory of adult rats. These results also indicate that postnatal PE could improve object recognition memory of non-spatial learning in adult rats. In addition, exercise

Bayesian feature weighting for unsupervised learning, with application to object recognition

OpenAIRE

Carbonetto , Peter; De Freitas , Nando; Gustafson , Paul; Thompson , Natalie

2003-01-01

International audience; We present a method for variable selection/weighting in an unsupervised learning context using Bayesian shrinkage. The basis for the model parameters and cluster assignments can be computed simultaneous using an efficient EM algorithm. Applying our Bayesian shrinkage model to a complex problem in object recognition (Duygulu, Barnard, de Freitas and Forsyth 2002), our experiments yied good results.

Marked Object Recognition Multitouch Screen Printed Touchpad for Interactive Applications.

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Nunes, Jivago Serrado; Castro, Nelson; Gonçalves, Sergio; Pereira, Nélson; Correia, Vitor; Lanceros-Mendez, Senentxu

2017-12-01

The market for interactive platforms is rapidly growing, and touchscreens have been incorporated in an increasing number of devices. Thus, the area of smart objects and devices is strongly increasing by adding interactive touch and multimedia content, leading to new uses and capabilities. In this work, a flexible screen printed sensor matrix is fabricated based on silver ink in a polyethylene terephthalate (PET) substrate. Diamond shaped capacitive electrodes coupled with conventional capacitive reading electronics enables fabrication of a highly functional capacitive touchpad, and also allows for the identification of marked objects. For the latter, the capacitive signatures are identified by intersecting points and distances between them. Thus, this work demonstrates the applicability of a low cost method using royalty-free geometries and technologies for the development of flexible multitouch touchpads for the implementation of interactive and object recognition applications.

Marked Object Recognition Multitouch Screen Printed Touchpad for Interactive Applications

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Jivago Serrado Nunes

2017-12-01

Full Text Available The market for interactive platforms is rapidly growing, and touchscreens have been incorporated in an increasing number of devices. Thus, the area of smart objects and devices is strongly increasing by adding interactive touch and multimedia content, leading to new uses and capabilities. In this work, a flexible screen printed sensor matrix is fabricated based on silver ink in a polyethylene terephthalate (PET substrate. Diamond shaped capacitive electrodes coupled with conventional capacitive reading electronics enables fabrication of a highly functional capacitive touchpad, and also allows for the identification of marked objects. For the latter, the capacitive signatures are identified by intersecting points and distances between them. Thus, this work demonstrates the applicability of a low cost method using royalty-free geometries and technologies for the development of flexible multitouch touchpads for the implementation of interactive and object recognition applications.

Asymmetric Functional Connectivity of the Contra- and Ipsilateral Secondary Somatosensory Cortex during Tactile Object Recognition

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Yinghua Yu

2018-01-01

Full Text Available In the somatosensory system, it is well known that the bilateral secondary somatosensory cortex (SII receives projections from the unilateral primary somatosensory cortex (SI, and the SII, in turn, sends feedback projections to SI. Most neuroimaging studies have clearly shown bilateral SII activation using only unilateral stimulation for both anatomical and functional connectivity across SII subregions. However, no study has unveiled differences in the functional connectivity of the contra- and ipsilateral SII network that relates to frontoparietal areas during tactile object recognition. Therefore, we used event-related functional magnetic resonance imaging (fMRI and a delayed match-to-sample (DMS task to investigate the contributions of bilateral SII during tactile object recognition. In the fMRI experiment, 14 healthy subjects were presented with tactile angle stimuli on their right index finger and asked to encode three sample stimuli during the encoding phase and one test stimulus during the recognition phase. Then, the subjects indicated whether the angle of test stimulus was presented during the encoding phase. The results showed that contralateral (left SII activity was greater than ipsilateral (right SII activity during the encoding phase, but there was no difference during the recognition phase. A subsequent psycho-physiological interaction (PPI analysis revealed distinct connectivity from the contra- and ipsilateral SII to other regions. The left SII functionally connected to the left SI and right primary and premotor cortex, while the right SII functionally connected to the left posterior parietal cortex (PPC. Our findings suggest that in situations involving unilateral tactile object recognition, contra- and ipsilateral SII will induce an asymmetrical functional connectivity to other brain areas, which may occur by the hand contralateral effect of SII.

The active blind spot camera: hard real-time recognition of moving objects from a moving camera

OpenAIRE

Van Beeck, Kristof; Goedemé, Toon; Tuytelaars, Tinne

2014-01-01

This PhD research focuses on visual object recognition under specific demanding conditions. The object to be recognized as well as the camera move, and the time available for the recognition task is extremely short. This generic problem is applied here on a specific problem: the active blind spot camera. Statistics show a large number of accidents with trucks are related to the so-called blind spot, the area around the vehicle in which vulnerable road users are hard to perceive by the truck d...

Invariant object recognition based on the generalized discrete radon transform

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Easley, Glenn R.; Colonna, Flavia

2004-04-01

We introduce a method for classifying objects based on special cases of the generalized discrete Radon transform. We adjust the transform and the corresponding ridgelet transform by means of circular shifting and a singular value decomposition (SVD) to obtain a translation, rotation and scaling invariant set of feature vectors. We then use a back-propagation neural network to classify the input feature vectors. We conclude with experimental results and compare these with other invariant recognition methods.

A reciprocal model of face recognition and autistic traits: evidence from an individual differences perspective.

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Halliday, Drew W R; MacDonald, Stuart W S; Scherf, K Suzanne; Sherf, Suzanne K; Tanaka, James W

2014-01-01

Although not a core symptom of the disorder, individuals with autism often exhibit selective impairments in their face processing abilities. Importantly, the reciprocal connection between autistic traits and face perception has rarely been examined within the typically developing population. In this study, university participants from the social sciences, physical sciences, and humanities completed a battery of measures that assessed face, object and emotion recognition abilities, general perceptual-cognitive style, and sub-clinical autistic traits (the Autism Quotient (AQ)). We employed separate hierarchical multiple regression analyses to evaluate which factors could predict face recognition scores and AQ scores. Gender, object recognition performance, and AQ scores predicted face recognition behaviour. Specifically, males, individuals with more autistic traits, and those with lower object recognition scores performed more poorly on the face recognition test. Conversely, university major, gender and face recognition performance reliably predicted AQ scores. Science majors, males, and individuals with poor face recognition skills showed more autistic-like traits. These results suggest that the broader autism phenotype is associated with lower face recognition abilities, even among typically developing individuals.

Glucocorticoid effects on object recognition memory require training-associated emotional arousal

OpenAIRE

Okuda, Shoki; Roozendaal, Benno; McGaugh, James L.

2004-01-01

Considerable evidence implicates glucocorticoid hormones in the regulation of memory consolidation and memory retrieval. The present experiments investigated whether the influence of these hormones on memory depends on the level of emotional arousal induced by the training experience. We investigated this issue in male Sprague–Dawley rats by examining the effects of immediate posttraining systemic injections of the glucocorticoid corticosterone on object recognition memory under two condition...

An Intelligent Systems Approach to Automated Object Recognition: A Preliminary Study

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Maddox, Brian G.; Swadley, Casey L.

2002-01-01

Attempts at fully automated object recognition systems have met with varying levels of success over the years. However, none of the systems have achieved high enough accuracy rates to be run unattended. One of the reasons for this may be that they are designed from the computer's point of view and rely mainly on image-processing methods. A better solution to this problem may be to make use of modern advances in computational intelligence and distributed processing to try to mimic how the human brain is thought to recognize objects. As humans combine cognitive processes with detection techniques, such a system would combine traditional image-processing techniques with computer-based intelligence to determine the identity of various objects in a scene.

Multispectral image analysis for object recognition and classification

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Viau, C. R.; Payeur, P.; Cretu, A.-M.

2016-05-01

Computer and machine vision applications are used in numerous fields to analyze static and dynamic imagery in order to assist or automate decision-making processes. Advancements in sensor technologies now make it possible to capture and visualize imagery at various wavelengths (or bands) of the electromagnetic spectrum. Multispectral imaging has countless applications in various fields including (but not limited to) security, defense, space, medical, manufacturing and archeology. The development of advanced algorithms to process and extract salient information from the imagery is a critical component of the overall system performance. The fundamental objective of this research project was to investigate the benefits of combining imagery from the visual and thermal bands of the electromagnetic spectrum to improve the recognition rates and accuracy of commonly found objects in an office setting. A multispectral dataset (visual and thermal) was captured and features from the visual and thermal images were extracted and used to train support vector machine (SVM) classifiers. The SVM's class prediction ability was evaluated separately on the visual, thermal and multispectral testing datasets.

HONTIOR - HIGHER-ORDER NEURAL NETWORK FOR TRANSFORMATION INVARIANT OBJECT RECOGNITION

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Spirkovska, L.

1994-01-01

Neural networks have been applied in numerous fields, including transformation invariant object recognition, wherein an object is recognized despite changes in the object's position in the input field, size, or rotation. One of the more successful neural network methods used in invariant object recognition is the higher-order neural network (HONN) method. With a HONN, known relationships are exploited and the desired invariances are built directly into the architecture of the network, eliminating the need for the network to learn invariance to transformations. This results in a significant reduction in the training time required, since the network needs to be trained on only one view of each object, not on numerous transformed views. Moreover, one hundred percent accuracy is guaranteed for images characterized by the built-in distortions, providing noise is not introduced through pixelation. The program HONTIOR implements a third-order neural network having invariance to translation, scale, and in-plane rotation built directly into the architecture, Thus, for 2-D transformation invariance, the network needs only to be trained on just one view of each object. HONTIOR can also be used for 3-D transformation invariant object recognition by training the network only on a set of out-of-plane rotated views. Historically, the major drawback of HONNs has been that the size of the input field was limited to the memory required for the large number of interconnections in a fully connected network. HONTIOR solves this problem by coarse coding the input images (coding an image as a set of overlapping but offset coarser images). Using this scheme, large input fields (4096 x 4096 pixels) can easily be represented using very little virtual memory (30Mb). The HONTIOR distribution consists of three main programs. The first program contains the training and testing routines for a third-order neural network. The second program contains the same training and testing procedures as the

Selective attention affects conceptual object priming and recognition: a study with young and older adults.

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Ballesteros, Soledad; Mayas, Julia

2014-01-01

In the present study, we investigated the effects of selective attention at encoding on conceptual object priming (Experiment 1) and old-new recognition memory (Experiment 2) tasks in young and older adults. The procedures of both experiments included encoding and memory test phases separated by a short delay. At encoding, the picture outlines of two familiar objects, one in blue and the other in green, were presented to the left and to the right of fixation. In Experiment 1, participants were instructed to attend to the picture outline of a certain color and to classify the object as natural or artificial. After a short delay, participants performed a natural/artificial speeded conceptual classification task with repeated attended, repeated unattended, and new pictures. In Experiment 2, participants at encoding memorized the attended pictures and classify them as natural or artificial. After the encoding phase, they performed an old-new recognition memory task. Consistent with previous findings with perceptual priming tasks, we found that conceptual object priming, like explicit memory, required attention at encoding. Significant priming was obtained in both age groups, but only for those pictures that were attended at encoding. Although older adults were slower than young adults, both groups showed facilitation for attended pictures. In line with previous studies, young adults had better recognition memory than older adults.

Selective attention affects conceptual object priming and recognition: A study with young and older adults

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Soledad eBallesteros

2015-01-01

Full Text Available In the present study, we investigated the effects of selective attention at encoding on conceptual object priming (Experiment 1 and old-new recognition memory (Experiment 2 tasks in young and older adults. The procedures of both experiments included encoding and memory test phases separated by a short delay. At encoding, the picture outlines of two familiar objects, one in blue and the other in green, were presented to the left and to the right of fixation. In Experiment 1, participants were instructed to attend to the picture outline of a certain color and to classify the object as natural or artificial. After a short delay, participants performed a natural/ artificial speeded conceptual classification task with repeated attended, repeated unattended and new pictures. In Experiment 2, participants at encoding memorized the attended pictures and classified them as natural or artificial. After the encoding phase, they performed an old-new recognition memory task. Consistent with previous findings with perceptual priming tasks, we found that conceptual object priming, like explicit memory, required attention at encoding. Significant priming was obtained in both age groups, but only for those pictures that were attended at encoding. Although older adults were slower than young adults, both groups showed facilitation for attended pictures. In line with previous studies, young adults had better recognition memory than older adults.

Emotion Recognition Ability Test Using JACFEE Photos: A Validity/Reliability Study of a War Veterans' Sample and Their Offspring.

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Castro-Vale, Ivone; Severo, Milton; Carvalho, Davide; Mota-Cardoso, Rui

2015-01-01

Emotion recognition is very important for social interaction. Several mental disorders influence facial emotion recognition. War veterans and their offspring are subject to an increased risk of developing psychopathology. Emotion recognition is an important aspect that needs to be addressed in this population. To our knowledge, no test exists that is validated for use with war veterans and their offspring. The current study aimed to validate the JACFEE photo set to study facial emotion recognition in war veterans and their offspring. The JACFEE photo set was presented to 135 participants, comprised of 62 male war veterans and 73 war veterans' offspring. The participants identified the facial emotion presented from amongst the possible seven emotions that were tested for: anger, contempt, disgust, fear, happiness, sadness, and surprise. A loglinear model was used to evaluate whether the agreement between the intended and the chosen emotions was higher than the expected. Overall agreement between chosen and intended emotions was 76.3% (Cohen kappa = 0.72). The agreement ranged from 63% (sadness expressions) to 91% (happiness expressions). The reliability by emotion ranged from 0.617 to 0.843 and the overall JACFEE photo set Cronbach alpha was 0.911. The offspring showed higher agreement when compared with the veterans (RR: 41.52 vs 12.12, p < 0.001), which confirms the construct validity of the test. The JACFEE set of photos showed good validity and reliability indices, which makes it an adequate instrument for researching emotion recognition ability in the study sample of war veterans and their respective offspring.

Emotion Recognition Ability Test Using JACFEE Photos: A Validity/Reliability Study of a War Veterans' Sample and Their Offspring.

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Ivone Castro-Vale

Full Text Available Emotion recognition is very important for social interaction. Several mental disorders influence facial emotion recognition. War veterans and their offspring are subject to an increased risk of developing psychopathology. Emotion recognition is an important aspect that needs to be addressed in this population. To our knowledge, no test exists that is validated for use with war veterans and their offspring. The current study aimed to validate the JACFEE photo set to study facial emotion recognition in war veterans and their offspring. The JACFEE photo set was presented to 135 participants, comprised of 62 male war veterans and 73 war veterans' offspring. The participants identified the facial emotion presented from amongst the possible seven emotions that were tested for: anger, contempt, disgust, fear, happiness, sadness, and surprise. A loglinear model was used to evaluate whether the agreement between the intended and the chosen emotions was higher than the expected. Overall agreement between chosen and intended emotions was 76.3% (Cohen kappa = 0.72. The agreement ranged from 63% (sadness expressions to 91% (happiness expressions. The reliability by emotion ranged from 0.617 to 0.843 and the overall JACFEE photo set Cronbach alpha was 0.911. The offspring showed higher agreement when compared with the veterans (RR: 41.52 vs 12.12, p < 0.001, which confirms the construct validity of the test. The JACFEE set of photos showed good validity and reliability indices, which makes it an adequate instrument for researching emotion recognition ability in the study sample of war veterans and their respective offspring.

Intracellular Zn(2+) signaling in the dentate gyrus is required for object recognition memory.

Science.gov (United States)

Takeda, Atsushi; Tamano, Haruna; Ogawa, Taisuke; Takada, Shunsuke; Nakamura, Masatoshi; Fujii, Hiroaki; Ando, Masaki

2014-11-01

The role of perforant pathway-dentate granule cell synapses in cognitive behavior was examined focusing on synaptic Zn(2+) signaling in the dentate gyrus. Object recognition memory was transiently impaired when extracellular Zn(2+) levels were decreased by injection of clioquinol and N,N,N',N'-tetrakis-(2-pyridylmethyl) ethylendediamine. To pursue the effect of the loss and/or blockade of Zn(2+) signaling in dentate granule cells, ZnAF-2DA (100 pmol, 0.1 mM/1 µl), an intracellular Zn(2+) chelator, was locally injected into the dentate molecular layer of rats. ZnAF-2DA injection, which was estimated to chelate intracellular Zn(2+) signaling only in the dentate gyrus, affected object recognition memory 1 h after training without affecting intracellular Ca(2+) signaling in the dentate molecular layer. In vivo dentate gyrus long-term potentiation (LTP) was affected under the local perfusion of the recording region (the dentate granule cell layer) with 0.1 mM ZnAF-2DA, but not with 1-10 mM CaEDTA, an extracellular Zn(2+) chelator, suggesting that the blockade of intracellular Zn(2+) signaling in dentate granule cells affects dentate gyrus LTP. The present study demonstrates that intracellular Zn(2+) signaling in the dentate gyrus is required for object recognition memory, probably via dentate gyrus LTP expression. Copyright © 2014 Wiley Periodicals, Inc.

Modified-hybrid optical neural network filter for multiple object recognition within cluttered scenes

Science.gov (United States)

Kypraios, Ioannis; Young, Rupert C. D.; Chatwin, Chris R.

2009-08-01

Motivated by the non-linear interpolation and generalization abilities of the hybrid optical neural network filter between the reference and non-reference images of the true-class object we designed the modifiedhybrid optical neural network filter. We applied an optical mask to the hybrid optical neural network's filter input. The mask was built with the constant weight connections of a randomly chosen image included in the training set. The resulted design of the modified-hybrid optical neural network filter is optimized for performing best in cluttered scenes of the true-class object. Due to the shift invariance properties inherited by its correlator unit the filter can accommodate multiple objects of the same class to be detected within an input cluttered image. Additionally, the architecture of the neural network unit of the general hybrid optical neural network filter allows the recognition of multiple objects of different classes within the input cluttered image by modifying the output layer of the unit. We test the modified-hybrid optical neural network filter for multiple objects of the same and of different classes' recognition within cluttered input images and video sequences of cluttered scenes. The filter is shown to exhibit with a single pass over the input data simultaneously out-of-plane rotation, shift invariance and good clutter tolerance. It is able to successfully detect and classify correctly the true-class objects within background clutter for which there has been no previous training.

Chronic prenatal caffeine exposure impairs novel object recognition and radial arm maze behaviors in adult rats.

Science.gov (United States)

Soellner, Deborah E; Grandys, Theresa; Nuñez, Joseph L

2009-12-14

In this report, we demonstrate that chronic prenatal exposure to a moderate dose of caffeine disrupts novel object recognition and radial arm maze behaviors in adult male and female rats. Pregnant dams were administered either tap water or 75 mg/L caffeinated tap water throughout gestation. Oral self-administration in the drinking water led to an approximate maternal intake of 10mg/kg/day, equivalent to 2-3 cups of coffee/day in humans based on a metabolic body weight conversion. In adulthood, the offspring underwent testing on novel object recognition, radial arm maze, and Morris water maze tasks. Prenatal caffeine exposure was found to impair 24-h memory retention in the novel object recognition task and impair both working and reference memory in the radial arm maze. However, prenatal caffeine exposure did not alter Morris water maze performance in either a simple water maze procedure or in an advanced water maze procedure that included reversal and working memory paradigms. These findings demonstrate that chronic oral intake of caffeine throughout gestation can alter adult cognitive behaviors in rats.

Biased figure-ground assignment affects conscious object recognition in spatial neglect.

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Eramudugolla, Ranmalee; Driver, Jon; Mattingley, Jason B

2010-09-01

Unilateral spatial neglect is a disorder of attention and spatial representation, in which early visual processes such as figure-ground segmentation have been assumed to be largely intact. There is evidence, however, that the spatial attention bias underlying neglect can bias the segmentation of a figural region from its background. Relatively few studies have explicitly examined the effect of spatial neglect on processing the figures that result from such scene segmentation. Here, we show that a neglect patient's bias in figure-ground segmentation directly influences his conscious recognition of these figures. By varying the relative salience of figural and background regions in static, two-dimensional displays, we show that competition between elements in such displays can modulate a neglect patient's ability to recognise parsed figures in a scene. The findings provide insight into the interaction between scene segmentation, explicit object recognition, and attention.

Humans and Deep Networks Largely Agree on Which Kinds of Variation Make Object Recognition Harder.

Science.gov (United States)

Kheradpisheh, Saeed R; Ghodrati, Masoud; Ganjtabesh, Mohammad; Masquelier, Timothée

2016-01-01

View-invariant object recognition is a challenging problem that has attracted much attention among the psychology, neuroscience, and computer vision communities. Humans are notoriously good at it, even if some variations are presumably more difficult to handle than others (e.g., 3D rotations). Humans are thought to solve the problem through hierarchical processing along the ventral stream, which progressively extracts more and more invariant visual features. This feed-forward architecture has inspired a new generation of bio-inspired computer vision systems called deep convolutional neural networks (DCNN), which are currently the best models for object recognition in natural images. Here, for the first time, we systematically compared human feed-forward vision and DCNNs at view-invariant object recognition task using the same set of images and controlling the kinds of transformation (position, scale, rotation in plane, and rotation in depth) as well as their magnitude, which we call "variation level." We used four object categories: car, ship, motorcycle, and animal. In total, 89 human subjects participated in 10 experiments in which they had to discriminate between two or four categories after rapid presentation with backward masking. We also tested two recent DCNNs (proposed respectively by Hinton's group and Zisserman's group) on the same tasks. We found that humans and DCNNs largely agreed on the relative difficulties of each kind of variation: rotation in depth is by far the hardest transformation to handle, followed by scale, then rotation in plane, and finally position (much easier). This suggests that DCNNs would be reasonable models of human feed-forward vision. In addition, our results show that the variation levels in rotation in depth and scale strongly modulate both humans' and DCNNs' recognition performances. We thus argue that these variations should be controlled in the image datasets used in vision research.

Humans and deep networks largely agree on which kinds of variation make object recognition harder

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Saeed Reza Kheradpisheh

2016-08-01

Full Text Available View-invariant object recognition is a challenging problem that has attracted much attention among the psychology, neuroscience, and computer vision communities. Humans are notoriously good at it, even if some variations are presumably more difficult to handle than others (e.g. 3D rotations. Humans are thought to solve the problem through hierarchical processing along the ventral stream, which progressively extracts more and more invariant visual features. This feed-forward architecture has inspired a new generation of bio-inspired computer vision systems called deep convolutional neural networks (DCNN, which are currently the best models for object recognition in natural images. Here, for the first time, we systematically compared human feed-forward vision and DCNNs at view-invariant object recognition task using the same set of images and controlling the kinds of transformation (position, scale, rotation in plane, and rotation in depth as well as their magnitude, which we call variation level. We used four object categories: car, ship, motorcycle, and animal. In total, 89 human subjects participated in 10 experiments in which they had to discriminate between two or four categories after rapid presentation with backward masking. We also tested two recent DCNNs (proposed respectively by Hinton's group and Zisserman's group on the same tasks. We found that humans and DCNNs largely agreed on the relative difficulties of each kind of variation: rotation in depth is by far the hardest transformation to handle, followed by scale, then rotation in plane, and finally position (much easier. This suggests that DCNNs would be reasonable models of human feed-forward vision. In addition, our results show that the variation levels in rotation in depth and scale strongly modulate both humans' and DCNNs' recognition performances. We thus argue that these variations should be controlled in the image datasets used in vision research.

Object detection and recognition in digital images theory and practice

CERN Document Server

Cyganek, Boguslaw

2013-01-01

Object detection, tracking and recognition in images are key problems in computer vision. This book provides the reader with a balanced treatment between the theory and practice of selected methods in these areas to make the book accessible to a range of researchers, engineers, developers and postgraduate students working in computer vision and related fields. Key features: Explains the main theoretical ideas behind each method (which are augmented with a rigorous mathematical derivation of the formulas), their implementation (in C++) and demonstrated working in real applications.

Acoustic signature recognition technique for Human-Object Interactions (HOI) in persistent surveillance systems

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Alkilani, Amjad; Shirkhodaie, Amir

2013-05-01

Handling, manipulation, and placement of objects, hereon called Human-Object Interaction (HOI), in the environment generate sounds. Such sounds are readily identifiable by the human hearing. However, in the presence of background environment noises, recognition of minute HOI sounds is challenging, though vital for improvement of multi-modality sensor data fusion in Persistent Surveillance Systems (PSS). Identification of HOI sound signatures can be used as precursors to detection of pertinent threats that otherwise other sensor modalities may miss to detect. In this paper, we present a robust method for detection and classification of HOI events via clustering of extracted features from training of HOI acoustic sound waves. In this approach, salient sound events are preliminary identified and segmented from background via a sound energy tracking method. Upon this segmentation, frequency spectral pattern of each sound event is modeled and its features are extracted to form a feature vector for training. To reduce dimensionality of training feature space, a Principal Component Analysis (PCA) technique is employed to expedite fast classification of test feature vectors, a kd-tree and Random Forest classifiers are trained for rapid classification of training sound waves. Each classifiers employs different similarity distance matching technique for classification. Performance evaluations of classifiers are compared for classification of a batch of training HOI acoustic signatures. Furthermore, to facilitate semantic annotation of acoustic sound events, a scheme based on Transducer Mockup Language (TML) is proposed. The results demonstrate the proposed approach is both reliable and effective, and can be extended to future PSS applications.

The hierarchical brain network for face recognition.

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Zhen, Zonglei; Fang, Huizhen; Liu, Jia

2013-01-01

Numerous functional magnetic resonance imaging (fMRI) studies have identified multiple cortical regions that are involved in face processing in the human brain. However, few studies have characterized the face-processing network as a functioning whole. In this study, we used fMRI to identify face-selective regions in the entire brain and then explore the hierarchical structure of the face-processing network by analyzing functional connectivity among these regions. We identified twenty-five regions mainly in the occipital, temporal and frontal cortex that showed a reliable response selective to faces (versus objects) across participants and across scan sessions. Furthermore, these regions were clustered into three relatively independent sub-networks in a face-recognition task on the basis of the strength of functional connectivity among them. The functionality of the sub-networks likely corresponds to the recognition of individual identity, retrieval of semantic knowledge and representation of emotional information. Interestingly, when the task was switched to object recognition from face recognition, the functional connectivity between the inferior occipital gyrus and the rest of the face-selective regions were significantly reduced, suggesting that this region may serve as an entry node in the face-processing network. In sum, our study provides empirical evidence for cognitive and neural models of face recognition and helps elucidate the neural mechanisms underlying face recognition at the network level.

Short- and long-term effects of nicotine and the histone deacetylase inhibitor phenylbutyrate on novel object recognition in zebrafish.

Science.gov (United States)

Faillace, M P; Pisera-Fuster, A; Medrano, M P; Bejarano, A C; Bernabeu, R O

2017-03-01

Zebrafish have a sophisticated color- and shape-sensitive visual system, so we examined color cue-based novel object recognition in zebrafish. We evaluated preference in the absence or presence of drugs that affect attention and memory retention in rodents: nicotine and the histone deacetylase inhibitor (HDACi) phenylbutyrate (PhB). The objective of this study was to evaluate whether nicotine and PhB affect innate preferences of zebrafish for familiar and novel objects after short- and long-retention intervals. We developed modified object recognition (OR) tasks using neutral novel and familiar objects in different colors. We also tested objects which differed with respect to the exploratory behavior they elicited from naïve zebrafish. Zebrafish showed an innate preference for exploring red or green objects rather than yellow or blue objects. Zebrafish were better at discriminating color changes than changes in object shape or size. Nicotine significantly enhanced or changed short-term innate novel object preference whereas PhB had similar effects when preference was assessed 24 h after training. Analysis of other zebrafish behaviors corroborated these results. Zebrafish were innately reluctant or prone to explore colored novel objects, so drug effects on innate preference for objects can be evaluated changing the color of objects with a simple geometry. Zebrafish exhibited recognition memory for novel objects with similar innate significance. Interestingly, nicotine and PhB significantly modified innate object preference.

Depth Value Pre-Processing for Accurate Transfer Learning Based RGB-D Object Recognition

DEFF Research Database (Denmark)

Aakerberg, Andreas; Nasrollahi, Kamal; Rasmussen, Christoffer Bøgelund

2017-01-01

of an existing deeplearning based RGB-D object recognition model, namely the FusionNet proposed by Eitel et al. First, we showthat encoding the depth values as colorized surface normals is beneficial, when the model is initialized withweights learned from training on ImageNet data. Additionally, we show...

Differential Roles for "Nr4a1" and "Nr4a2" in Object Location vs. Object Recognition Long-Term Memory

Science.gov (United States)

McNulty, Susan E.; Barrett, Ruth M.; Vogel-Ciernia, Annie; Malvaez, Melissa; Hernandez, Nicole; Davatolhagh, M. Felicia; Matheos, Dina P.; Schiffman, Aaron; Wood, Marcelo A.

2012-01-01

"Nr4a1" and "Nr4a2" are transcription factors and immediate early genes belonging to the nuclear receptor Nr4a family. In this study, we examine their role in long-term memory formation for object location and object recognition. Using siRNA to block expression of either "Nr4a1" or "Nr4a2", we found that "Nr4a2" is necessary for both long-term…

Perirhinal Cortex Resolves Feature Ambiguity in Configural Object Recognition and Perceptual Oddity Tasks

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Bartko, Susan J.; Winters, Boyer D.; Cowell, Rosemary A.; Saksida, Lisa M.; Bussey, Timothy J.

2007-01-01

The perirhinal cortex (PRh) has a well-established role in object recognition memory. More recent studies suggest that PRh is also important for two-choice visual discrimination tasks. Specifically, it has been suggested that PRh contains conjunctive representations that help resolve feature ambiguity, which occurs when a task cannot easily be…

Coarse-coded higher-order neural networks for PSRI object recognition. [position, scale, and rotation invariant

Science.gov (United States)

Spirkovska, Lilly; Reid, Max B.

1993-01-01

A higher-order neural network (HONN) can be designed to be invariant to changes in scale, translation, and inplane rotation. Invariances are built directly into the architecture of a HONN and do not need to be learned. Consequently, fewer training passes and a smaller training set are required to learn to distinguish between objects. The size of the input field is limited, however, because of the memory required for the large number of interconnections in a fully connected HONN. By coarse coding the input image, the input field size can be increased to allow the larger input scenes required for practical object recognition problems. We describe a coarse coding technique and present simulation results illustrating its usefulness and its limitations. Our simulations show that a third-order neural network can be trained to distinguish between two objects in a 4096 x 4096 pixel input field independent of transformations in translation, in-plane rotation, and scale in less than ten passes through the training set. Furthermore, we empirically determine the limits of the coarse coding technique in the object recognition domain.

Short-term blueberry-enriched antioxidant diet prevents and reverses object recognition memory loss in aged rats

Science.gov (United States)

Objective Previously, four months of a blueberry-enriched (BB) antioxidant diet prevented impaired object recognition memory in aged rats. Experiment 1 determined whether one and two-month BB diets would have a similar effect and whether the benefits would disappear promptly after terminating the d...

The medial prefrontal cortex-lateral entorhinal cortex circuit is essential for episodic-like memory and associative object-recognition.

Science.gov (United States)

Chao, Owen Y; Huston, Joseph P; Li, Jay-Shake; Wang, An-Li; de Souza Silva, Maria A

2016-05-01

The prefrontal cortex directly projects to the lateral entorhinal cortex (LEC), an important substrate for engaging item-associated information and relaying the information to the hippocampus. Here we ask to what extent the communication between the prefrontal cortex and LEC is critically involved in the processing of episodic-like memory. We applied a disconnection procedure to test whether the interaction between the medial prefrontal cortex (mPFC) and LEC is essential for the expression of recognition memory. It was found that male rats that received unilateral NMDA lesions of the mPFC and LEC in the same hemisphere, exhibited intact episodic-like (what-where-when) and object-recognition memories. When these lesions were placed in the opposite hemispheres (disconnection), episodic-like and associative memories for object identity, location and context were impaired. However, the disconnection did not impair the components of episodic memory, namely memory for novel object (what), object place (where) and temporal order (when), per se. Thus, the present findings suggest that the mPFC and LEC are a critical part of a neural circuit that underlies episodic-like and associative object-recognition memory. © 2015 Wiley Periodicals, Inc.

New technique for real-time distortion-invariant multiobject recognition and classification

Science.gov (United States)

Hong, Rutong; Li, Xiaoshun; Hong, En; Wang, Zuyi; Wei, Hongan

2001-04-01

A real-time hybrid distortion-invariant OPR system was established to make 3D multiobject distortion-invariant automatic pattern recognition. Wavelet transform technique was used to make digital preprocessing of the input scene, to depress the noisy background and enhance the recognized object. A three-layer backpropagation artificial neural network was used in correlation signal post-processing to perform multiobject distortion-invariant recognition and classification. The C-80 and NOA real-time processing ability and the multithread programming technology were used to perform high speed parallel multitask processing and speed up the post processing rate to ROIs. The reference filter library was constructed for the distortion version of 3D object model images based on the distortion parameter tolerance measuring as rotation, azimuth and scale. The real-time optical correlation recognition testing of this OPR system demonstrates that using the preprocessing, post- processing, the nonlinear algorithm os optimum filtering, RFL construction technique and the multithread programming technology, a high possibility of recognition and recognition rate ere obtained for the real-time multiobject distortion-invariant OPR system. The recognition reliability and rate was improved greatly. These techniques are very useful to automatic target recognition.

New neural-networks-based 3D object recognition system

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Abolmaesumi, Purang; Jahed, M.

1997-09-01

Three-dimensional object recognition has always been one of the challenging fields in computer vision. In recent years, Ulman and Basri (1991) have proposed that this task can be done by using a database of 2-D views of the objects. The main problem in their proposed system is that the correspondent points should be known to interpolate the views. On the other hand, their system should have a supervisor to decide which class does the represented view belong to. In this paper, we propose a new momentum-Fourier descriptor that is invariant to scale, translation, and rotation. This descriptor provides the input feature vectors to our proposed system. By using the Dystal network, we show that the objects can be classified with over 95% precision. We have used this system to classify the objects like cube, cone, sphere, torus, and cylinder. Because of the nature of the Dystal network, this system reaches to its stable point by a single representation of the view to the system. This system can also classify the similar views to a single class (e.g., for the cube, the system generated 9 different classes for 50 different input views), which can be used to select an optimum database of training views. The system is also very flexible to the noise and deformed views.

Recognition of Simple 3D Geometrical Objects under Partial Occlusion

Science.gov (United States)

Barchunova, Alexandra; Sommer, Gerald

In this paper we present a novel procedure for contour-based recognition of partially occluded three-dimensional objects. In our approach we use images of real and rendered objects whose contours have been deformed by a restricted change of the viewpoint. The preparatory part consists of contour extraction, preprocessing, local structure analysis and feature extraction. The main part deals with an extended construction and functionality of the classifier ensemble Adaptive Occlusion Classifier (AOC). It relies on a hierarchical fragmenting algorithm to perform a local structure analysis which is essential when dealing with occlusions. In the experimental part of this paper we present classification results for five classes of simple geometrical figures: prism, cylinder, half cylinder, a cube, and a bridge. We compare classification results for three classical feature extractors: Fourier descriptors, pseudo Zernike and Zernike moments.

The use of the Emotional-Object Recognition as an assay to assess learning and memory associated to an aversive stimulus in rodents.

Science.gov (United States)

Brancato, Anna; Lavanco, Gianluca; Cavallaro, Angela; Plescia, Fulvio; Cannizzaro, Carla

2016-12-01

Emotionally salient experiences induce the formation of explicit memory traces, besides eliciting automatic or implicit emotional memory in rodents. This study aims at investigating the implementation of a novel task for studying the formation of limbic memory engrams as a result of the acquisition- and retrieval- of fear-conditioning - biased declarative memory traces, measured by animal discrimination of an "emotional-object". Moreover, by using this new method we investigated the potential interactions between stimulation of cannabinoid transmission and integration of emotional information and cognitive functioning. The Emotional-Object Recognition task is composed of 3 following sessions: habituation; cued fear-conditioned learning; emotional recognition. Rats are exposed to Context "B chamber" for habituation and cued fear-conditioning, and tested in Context "A chamber" for emotional-object recognition. Cued fear-conditioning induces a reduction in emotional-object exploration time during the Emotional-Object Recognition task in controls. The activation of cannabinoid signalling impairs limbic memory formation, with respect to vehicle. The Emotional-Object Recognition test overcomes several limitations of commonly employed methods that explore declarative-, spatial memory and fear-conditioning in a non-integrated manner. It allows the assessment of unbiased cognitive indicators of emotional learning and memory. The Emotional-Object Recognition task is a valuable tool for investigating whether, and at what extent, specific drugs or pathological conditions that interfere with the individual affective/emotional homeostasis, can modulate the formation of emotionally salient explicit memory traces, thus jeopardizing control and regulation of animal behavioural strategy. Copyright © 2016 Elsevier B.V. All rights reserved.

New automated procedure to assess context recognition memory in mice.

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Reiss, David; Walter, Ondine; Bourgoin, Lucie; Kieffer, Brigitte L; Ouagazzal, Abdel-Mouttalib

2014-11-01

Recognition memory is an important aspect of human declarative memory and is one of the routine memory abilities altered in patients with amnestic syndrome and Alzheimer's disease. In rodents, recognition memory has been most widely assessed using the novel object preference paradigm, which exploits the spontaneous preference that animals display for novel objects. Here, we used nose-poke units instead of objects to design a simple automated method for assessing context recognition memory in mice. In the acquisition trial, mice are exposed for the first time to an operant chamber with one blinking nose-poke unit. In the choice session, a novel nonblinking nose-poke unit is inserted into an empty spatial location and the number of nose poking dedicated to each set of nose-poke unit is used as an index of recognition memory. We report that recognition performance varies as a function of the length of the acquisition period and the retention delay and is sensitive to conventional amnestic treatments. By manipulating the features of the operant chamber during a brief retrieval episode (3-min long), we further demonstrate that reconsolidation of the original contextual memory depends on the magnitude and the type of environmental changes introduced into the familiar spatial environment. These results show that the nose-poke recognition task provides a rapid and reliable way for assessing context recognition memory in mice and offers new possibilities for the deciphering of the brain mechanisms governing the reconsolidation process.

Automatic radar target recognition of objects falling on railway tracks

International Nuclear Information System (INIS)

Mroué, A; Heddebaut, M; Elbahhar, F; Rivenq, A; Rouvaen, J-M

2012-01-01

This paper presents an automatic radar target recognition procedure based on complex resonances using the signals provided by ultra-wideband radar. This procedure is dedicated to detection and identification of objects lying on railway tracks. For an efficient complex resonance extraction, a comparison between several pole extraction methods is illustrated. Therefore, preprocessing methods are presented aiming to remove most of the erroneous poles interfering with the discrimination scheme. Once physical poles are determined, a specific discrimination technique is introduced based on the Euclidean distances. Both simulation and experimental results are depicted showing an efficient discrimination of different targets including guided transport passengers

Object location and object recognition memory impairments, motivation deficits and depression in a model of Gulf War illness.

Science.gov (United States)

Hattiangady, Bharathi; Mishra, Vikas; Kodali, Maheedhar; Shuai, Bing; Rao, Xiolan; Shetty, Ashok K

2014-01-01

Memory and mood deficits are the enduring brain-related symptoms in Gulf War illness (GWI). Both animal model and epidemiological investigations have indicated that these impairments in a majority of GW veterans are linked to exposures to chemicals such as pyridostigmine bromide (PB, an antinerve gas drug), permethrin (PM, an insecticide) and DEET (a mosquito repellant) encountered during the Persian Gulf War-1. Our previous study in a rat model has shown that combined exposures to low doses of GWI-related (GWIR) chemicals PB, PM, and DEET with or without 5-min of restraint stress (a mild stress paradigm) causes hippocampus-dependent spatial memory dysfunction in a water maze test (WMT) and increased depressive-like behavior in a forced swim test (FST). In this study, using a larger cohort of rats exposed to GWIR-chemicals and stress, we investigated whether the memory deficiency identified earlier in a WMT is reproducible with an alternative and stress free hippocampus-dependent memory test such as the object location test (OLT). We also ascertained the possible co-existence of hippocampus-independent memory dysfunction using a novel object recognition test (NORT), and alterations in mood function with additional tests for motivation and depression. Our results provide new evidence that exposure to low doses of GWIR-chemicals and mild stress for 4 weeks causes deficits in hippocampus-dependent object location memory and perirhinal cortex-dependent novel object recognition memory. An open field test performed prior to other behavioral analyses revealed that memory impairments were not associated with increased anxiety or deficits in general motor ability. However, behavioral tests for mood function such as a voluntary physical exercise paradigm and a novelty suppressed feeding test (NSFT) demonstrated decreased motivation levels and depression. Thus, exposure to GWIR-chemicals and stress causes both hippocampus-dependent and hippocampus-independent memory

Blockade of intracellular Zn2+ signaling in the basolateral amygdala affects object recognition memory via attenuation of dentate gyrus LTP.

Science.gov (United States)

Fujise, Yuki; Kubota, Mitsuyasu; Suzuki, Miki; Tamano, Haruna; Takeda, Atsushi

2017-09-01

Hippocampus-dependent memory is modulated by the amygdala. However, it is unknown whether intracellular Zn 2+ signaling in the amygdala is involved in hippocampus-dependent memory. On the basis of the evidence that intracellular Zn 2+ signaling in dentate granule cells (DGC) is necessary for object recognition memory via LTP at medial perforant pathway (PP)-DGC synapses, the present study examined whether intracellular Zn 2+ signaling in the amygdala influences object recognition memory via modulation of LTP at medial PP-DGC synapses. When ZnAF-2DA (100 μM, 2 μl) was injected into the basolateral amygdala (BLA), intracellular ZnAF-2 locally chelated intracellular Zn 2+ in the amygdala. Recognition memory was affected when training of object recognition test was performed 20 min after ZnAF-2DA injection into the BLA. Twenty minutes after injection of ZnAF-2DA into the BLA, LTP induction at medial PP-DGC synapses was attenuated, while LTP induction at PP-BLA synapses was potentiated and LTP induction at BLA-DGC synapses was attenuated. These results suggest that intracellular Zn 2+ signaling in the BLA is involved in BLA-associated LTP and modulates LTP at medial PP-DGC synapses, followed by modulation of object recognition memory. Copyright © 2017 Elsevier Ltd. All rights reserved.

Using Markov Chains and Multi-Objective Optimization for Energy-Efficient Context Recognition

Directory of Open Access Journals (Sweden)

Vito Janko

2017-12-01

Full Text Available The recognition of the user’s context with wearable sensing systems is a common problem in ubiquitous computing. However, the typically small battery of such systems often makes continuous recognition impractical. The strain on the battery can be reduced if the sensor setting is adapted to each context. We propose a method that efficiently finds near-optimal sensor settings for each context. It uses Markov chains to simulate the behavior of the system in different configurations and the multi-objective genetic algorithm to find a set of good non-dominated configurations. The method was evaluated on three real-life datasets and found good trade-offs between the system’s energy expenditure and the system’s accuracy. One of the solutions, for example, consumed five-times less energy than the default one, while sacrificing only two percentage points of accuracy.

Using Markov Chains and Multi-Objective Optimization for Energy-Efficient Context Recognition.

Science.gov (United States)

Janko, Vito; Luštrek, Mitja

2017-12-29

The recognition of the user's context with wearable sensing systems is a common problem in ubiquitous computing. However, the typically small battery of such systems often makes continuous recognition impractical. The strain on the battery can be reduced if the sensor setting is adapted to each context. We propose a method that efficiently finds near-optimal sensor settings for each context. It uses Markov chains to simulate the behavior of the system in different configurations and the multi-objective genetic algorithm to find a set of good non-dominated configurations. The method was evaluated on three real-life datasets and found good trade-offs between the system's energy expenditure and the system's accuracy. One of the solutions, for example, consumed five-times less energy than the default one, while sacrificing only two percentage points of accuracy.

Reliability of a single objective measure in assessing sleepiness.

Science.gov (United States)

Sunwoo, Bernie Y; Jackson, Nicholas; Maislin, Greg; Gurubhagavatula, Indira; George, Charles F; Pack, Allan I

2012-01-01

To evaluate reliability of single objective tests in assessing sleepiness. Subjects who completed polysomnography underwent a 4-nap multiple sleep latency test (MSLT) the following day. Prior to each nap opportunity on MSLT, subjects performed the psychomotor vigilance test (PVT) and divided attention driving task (DADT). Results of single versus multiple test administrations were compared using the intraclass correlation coefficient (ICC) and adjusted for test administration order effects to explore time of day effects. Measures were explored as continuous and binary (i.e., impaired or not impaired). Community-based sample evaluated at a tertiary, university-based sleep center. 372 adult commercial vehicle operators oversampled for increased obstructive sleep apnea risk. N/A. AS CONTINUOUS MEASURES, ICC WERE AS FOLLOWS: MSLT 0.45, PVT median response time 0.69, PVT number of lapses 0.51, 10-min DADT tracking error 0.87, 20-min DADT tracking error 0.90. Based on binary outcomes, ICC were: MSLT 0.63, PVT number of lapses 0.85, 10-min DADT 0.95, 20-min DADT 0.96. Statistically significant time of day effects were seen in both the MSLT and PVT but not the DADT. Correlation between ESS and different objective tests was strongest for MSLT, range [-0.270 to -0.195] and persisted across all time points. Single DADT and PVT administrations are reliable measures of sleepiness. A single MSLT administration can reasonably discriminate individuals with MSL < 8 minutes. These results support the use of a single administration of some objective tests of sleepiness when performed under controlled conditions in routine clinical care.

Chronic methylphenidate-effects over circadian cycle of young and adult rats submitted to open-field and object recognition tests.

Science.gov (United States)

Gomes, Karin M; Souza, Renan P; Valvassori, Samira S; Réus, Gislaine Z; Inácio, Cecília G; Martins, Márcio R; Comim, Clarissa M; Quevedo, João

2009-11-01

In this study age-, circadian rhythm- and methylphenidate administration- effect on open field habituation and object recognition were analyzed. Young and adult male Wistar rats were treated with saline or methylphenidate 2.0 mg/kg for 28 days. Experiments were performed during the light and the dark cycle. Locomotor activity was significantly altered by circadian cycle and methylphenidate treatment during the training session and by drug treatment during the testing session. Exploratory activity was significantly modulated by age during the training session and by age and drug treatment during the testing session. Object recognition memory was altered by cycle at the training session; by age 1.5 h later and by cycle and age 24 h after the training session. These results show that methylphenidate treatment was the major modulator factor on open-field test while cycle and age had an important effect on object recognition experiment.

Object instance recognition using motion cues and instance specific appearance models

Science.gov (United States)

Schumann, Arne

2014-03-01

In this paper we present an object instance retrieval approach. The baseline approach consists of a pool of image features which are computed on the bounding boxes of a query object track and compared to a database of tracks in order to find additional appearances of the same object instance. We improve over this simple baseline approach in multiple ways: 1) we include motion cues to achieve improved robustness to viewpoint and rotation changes, 2) we include operator feedback to iteratively re-rank the resulting retrieval lists and 3) we use operator feedback and location constraints to train classifiers and learn an instance specific appearance model. We use these classifiers to further improve the retrieval results. The approach is evaluated on two popular public datasets for two different applications. We evaluate person re-identification on the CAVIAR shopping mall surveillance dataset and vehicle instance recognition on the VIVID aerial dataset and achieve significant improvements over our baseline results.

Classifier Fusion With Contextual Reliability Evaluation.

Science.gov (United States)

Liu, Zhunga; Pan, Quan; Dezert, Jean; Han, Jun-Wei; He, You

2018-05-01

Classifier fusion is an efficient strategy to improve the classification performance for the complex pattern recognition problem. In practice, the multiple classifiers to combine can have different reliabilities and the proper reliability evaluation plays an important role in the fusion process for getting the best classification performance. We propose a new method for classifier fusion with contextual reliability evaluation (CF-CRE) based on inner reliability and relative reliability concepts. The inner reliability, represented by a matrix, characterizes the probability of the object belonging to one class when it is classified to another class. The elements of this matrix are estimated from the -nearest neighbors of the object. A cautious discounting rule is developed under belief functions framework to revise the classification result according to the inner reliability. The relative reliability is evaluated based on a new incompatibility measure which allows to reduce the level of conflict between the classifiers by applying the classical evidence discounting rule to each classifier before their combination. The inner reliability and relative reliability capture different aspects of the classification reliability. The discounted classification results are combined with Dempster-Shafer's rule for the final class decision making support. The performance of CF-CRE have been evaluated and compared with those of main classical fusion methods using real data sets. The experimental results show that CF-CRE can produce substantially higher accuracy than other fusion methods in general. Moreover, CF-CRE is robust to the changes of the number of nearest neighbors chosen for estimating the reliability matrix, which is appealing for the applications.

Mechanisms and Neural Basis of Object and Pattern Recognition: A Study with Chess Experts

Science.gov (United States)

Bilalic, Merim; Langner, Robert; Erb, Michael; Grodd, Wolfgang

2010-01-01

Comparing experts with novices offers unique insights into the functioning of cognition, based on the maximization of individual differences. Here we used this expertise approach to disentangle the mechanisms and neural basis behind two processes that contribute to everyday expertise: object and pattern recognition. We compared chess experts and…

The Initial Development of Object Knowledge by a Learning Robot.

Science.gov (United States)

Modayil, Joseph; Kuipers, Benjamin

2008-11-30

We describe how a robot can develop knowledge of the objects in its environment directly from unsupervised sensorimotor experience. The object knowledge consists of multiple integrated representations: trackers that form spatio-temporal clusters of sensory experience, percepts that represent properties for the tracked objects, classes that support efficient generalization from past experience, and actions that reliably change object percepts. We evaluate how well this intrinsically acquired object knowledge can be used to solve externally specified tasks including object recognition and achieving goals that require both planning and continuous control.

Target recognition and scene interpretation in image/video understanding systems based on network-symbolic models

Science.gov (United States)

Kuvich, Gary

2004-08-01

Vision is only a part of a system that converts visual information into knowledge structures. These structures drive the vision process, resolving ambiguity and uncertainty via feedback, and provide image understanding, which is an interpretation of visual information in terms of these knowledge models. These mechanisms provide a reliable recognition if the object is occluded or cannot be recognized as a whole. It is hard to split the entire system apart, and reliable solutions to the target recognition problems are possible only within the solution of a more generic Image Understanding Problem. Brain reduces informational and computational complexities, using implicit symbolic coding of features, hierarchical compression, and selective processing of visual information. Biologically inspired Network-Symbolic representation, where both systematic structural/logical methods and neural/statistical methods are parts of a single mechanism, is the most feasible for such models. It converts visual information into relational Network-Symbolic structures, avoiding artificial precise computations of 3-dimensional models. Network-Symbolic Transformations derive abstract structures, which allows for invariant recognition of an object as exemplar of a class. Active vision helps creating consistent models. Attention, separation of figure from ground and perceptual grouping are special kinds of network-symbolic transformations. Such Image/Video Understanding Systems will be reliably recognizing targets.

Logarithmic r-θ mapping for hybrid optical neural network filter for multiple objects recognition within cluttered scenes

Science.gov (United States)

Kypraios, Ioannis; Young, Rupert C. D.; Chatwin, Chris R.; Birch, Phil M.

2009-04-01

θThe window unit in the design of the complex logarithmic r-θ mapping for hybrid optical neural network filter can allow multiple objects of the same class to be detected within the input image. Additionally, the architecture of the neural network unit of the complex logarithmic r-θ mapping for hybrid optical neural network filter becomes attractive for accommodating the recognition of multiple objects of different classes within the input image by modifying the output layer of the unit. We test the overall filter for multiple objects of the same and of different classes' recognition within cluttered input images and video sequences of cluttered scenes. Logarithmic r-θ mapping for hybrid optical neural network filter is shown to exhibit with a single pass over the input data simultaneously in-plane rotation, out-of-plane rotation, scale, log r-θ map translation and shift invariance, and good clutter tolerance by recognizing correctly the different objects within the cluttered scenes. We record in our results additional extracted information from the cluttered scenes about the objects' relative position, scale and in-plane rotation.

On hierarchical models for visual recognition and learning of objects, scenes, and activities

CERN Document Server

Spehr, Jens

2015-01-01

In many computer vision applications, objects have to be learned and recognized in images or image sequences. This book presents new probabilistic hierarchical models that allow an efficient representation of multiple objects of different categories, scales, rotations, and views. The idea is to exploit similarities between objects and object parts in order to share calculations and avoid redundant information. Furthermore inference approaches for fast and robust detection are presented. These new approaches combine the idea of compositional and similarity hierarchies and overcome limitations of previous methods. Besides classical object recognition the book shows the use for detection of human poses in a project for gait analysis. The use of activity detection is presented for the design of environments for ageing, to identify activities and behavior patterns in smart homes. In a presented project for parking spot detection using an intelligent vehicle, the proposed approaches are used to hierarchically model...

Novel object recognition ability in female mice following exposure to nanoparticle-rich diesel exhaust

Energy Technology Data Exchange (ETDEWEB)

Win-Shwe, Tin-Tin, E-mail: tin.tin.win.shwe@nies.go.jp [Center for Environmental Health Sciences, National Institute for Environmental Studies, 16‐2 Onogawa, Tsukuba, Ibaraki 305‐8506 (Japan); Fujimaki, Hidekazu; Fujitani, Yuji; Hirano, Seishiro [Center for Environmental Risk Research, National Institute for Environmental Studies, 16‐2 Onogawa, Tsukuba, Ibaraki 305‐8506 (Japan)

2012-08-01

Recently, our laboratory reported that exposure to nanoparticle-rich diesel exhaust (NRDE) for 3 months impaired hippocampus-dependent spatial learning ability and up-regulated the expressions of memory function-related genes in the hippocampus of female mice. However, whether NRDE affects the hippocampus-dependent non-spatial learning ability and the mechanism of NRDE-induced neurotoxicity was unknown. Female BALB/c mice were exposed to clean air, middle-dose NRDE (M-NRDE, 47 μg/m{sup 3}), high-dose NRDE (H-NRDE, 129 μg/m{sup 3}), or filtered H-NRDE (F-DE) for 3 months. We then investigated the effect of NRDE exposure on non-spatial learning ability and the expression of genes related to glutamate neurotransmission using a novel object recognition test and a real-time RT-PCR analysis, respectively. We also examined microglia marker Iba1 immunoreactivity in the hippocampus using immunohistochemical analyses. Mice exposed to H-NRDE or F-DE could not discriminate between familiar and novel objects. The control and M-NRDE-exposed groups showed a significantly increased discrimination index, compared to the H-NRDE-exposed group. Although no significant changes in the expression levels of the NMDA receptor subunits were observed, the expression of glutamate transporter EAAT4 was decreased and that of glutamic acid decarboxylase GAD65 was increased in the hippocampus of H-NRDE-exposed mice, compared with the expression levels in control mice. We also found that microglia activation was prominent in the hippocampal area of the H-NRDE-exposed mice, compared with the other groups. These results indicated that exposure to NRDE for 3 months impaired the novel object recognition ability. The present study suggests that genes related to glutamate metabolism may be involved in the NRDE-induced neurotoxicity observed in the present mouse model. -- Highlights: ► The effects of nanoparticle-induced neurotoxicity remain unclear. ► We investigated the effect of exposure to

Novel object recognition ability in female mice following exposure to nanoparticle-rich diesel exhaust

International Nuclear Information System (INIS)

Win-Shwe, Tin-Tin; Fujimaki, Hidekazu; Fujitani, Yuji; Hirano, Seishiro

2012-01-01

Recently, our laboratory reported that exposure to nanoparticle-rich diesel exhaust (NRDE) for 3 months impaired hippocampus-dependent spatial learning ability and up-regulated the expressions of memory function-related genes in the hippocampus of female mice. However, whether NRDE affects the hippocampus-dependent non-spatial learning ability and the mechanism of NRDE-induced neurotoxicity was unknown. Female BALB/c mice were exposed to clean air, middle-dose NRDE (M-NRDE, 47 μg/m 3 ), high-dose NRDE (H-NRDE, 129 μg/m 3 ), or filtered H-NRDE (F-DE) for 3 months. We then investigated the effect of NRDE exposure on non-spatial learning ability and the expression of genes related to glutamate neurotransmission using a novel object recognition test and a real-time RT-PCR analysis, respectively. We also examined microglia marker Iba1 immunoreactivity in the hippocampus using immunohistochemical analyses. Mice exposed to H-NRDE or F-DE could not discriminate between familiar and novel objects. The control and M-NRDE-exposed groups showed a significantly increased discrimination index, compared to the H-NRDE-exposed group. Although no significant changes in the expression levels of the NMDA receptor subunits were observed, the expression of glutamate transporter EAAT4 was decreased and that of glutamic acid decarboxylase GAD65 was increased in the hippocampus of H-NRDE-exposed mice, compared with the expression levels in control mice. We also found that microglia activation was prominent in the hippocampal area of the H-NRDE-exposed mice, compared with the other groups. These results indicated that exposure to NRDE for 3 months impaired the novel object recognition ability. The present study suggests that genes related to glutamate metabolism may be involved in the NRDE-induced neurotoxicity observed in the present mouse model. -- Highlights: ► The effects of nanoparticle-induced neurotoxicity remain unclear. ► We investigated the effect of exposure to

Infliximab ameliorates AD-associated object recognition memory impairment.

Science.gov (United States)

Kim, Dong Hyun; Choi, Seong-Min; Jho, Jihoon; Park, Man-Seok; Kang, Jisu; Park, Se Jin; Ryu, Jong Hoon; Jo, Jihoon; Kim, Hyun Hee; Kim, Byeong C

2016-09-15

Dysfunctions in the perirhinal cortex (PRh) are associated with visual recognition memory deficit, which is frequently detected in the early stage of Alzheimer's disease. Muscarinic acetylcholine receptor-dependent long-term depression (mAChR-LTD) of synaptic transmission is known as a key pathway in eliciting this type of memory, and Tg2576 mice expressing enhanced levels of Aβ oligomers are found to have impaired mAChR-LTD in this brain area at as early as 3 months of age. We found that the administration of Aβ oligomers in young normal mice also induced visual recognition memory impairment and perturbed mAChR-LTD in mouse PRh slices. In addition, when mice were treated with infliximab, a monoclonal antibody against TNF-α, visual recognition memory impaired by pre-administered Aβ oligomers dramatically improved and the detrimental Aβ effect on mAChR-LTD was annulled. Taken together, these findings suggest that Aβ-induced inflammation is mediated through TNF-α signaling cascades, disturbing synaptic transmission in the PRh, and leading to visual recognition memory deficits. Copyright © 2016 Elsevier B.V. All rights reserved.

Determination of the Reliability Function of Nonredundant Element of Power Object

International Nuclear Information System (INIS)

Namgaladze, D.; Kiziria, T.

2007-01-01

At considering the reliability indices of the system element with recovery, the time of operation and recovery is usually accounted for. But, in practice, there often occur the situations when, after the failure of the system (or its element), it takes considerable time to begin repairing (time for revealing the damages, time for organization of repairing work, delivery of spare parts etc.). The total dead time is called the waiting time. In the present work, the reliability indices of the element of power object with account for the waiting time are determined analytically by using Markovian processes. (author)

Is pupillary response a reliable index of word recognition? Evidence from a delayed lexical decision task.

Science.gov (United States)

Haro, Juan; Guasch, Marc; Vallès, Blanca; Ferré, Pilar

2017-10-01

Previous word recognition studies have shown that the pupillary response is sensitive to a word's frequency. However, such a pupillary effect may be due to the process of executing a response, instead of being an index of word processing. With the aim of exploring this possibility, we recorded the pupillary responses in two experiments involving a lexical decision task (LDT). In the first experiment, participants completed a standard LDT, whereas in the second they performed a delayed LDT. The delay in the response allowed us to compare pupil dilations with and without the response execution component. The results showed that pupillary response was modulated by word frequency in both the standard and the delayed LDT. This finding supports the reliability of using pupillometry for word recognition research. Importantly, our results also suggest that tasks that do not require a response during pupil recording lead to clearer and stronger effects.

Short-term blueberry-enriched diet prevents and reverses object recognition memory loss in aging rats.

Science.gov (United States)

Malin, David H; Lee, David R; Goyarzu, Pilar; Chang, Yu-Hsuan; Ennis, Lalanya J; Beckett, Elizabeth; Shukitt-Hale, Barbara; Joseph, James A

2011-03-01

Previously, 4 mo of a blueberry-enriched (BB) antioxidant diet prevented impaired object recognition memory in aging rats. Experiment 1 determined whether 1- and 2-mo BB diets would have a similar effect and whether the benefits would disappear promptly after terminating the diets. Experiment 2 determined whether a 1-mo BB diet could subsequently reverse existing object memory impairment in aging rats. In experiment 1, Fischer-344 rats were maintained on an appropriate control diet or on 1 or 2 mo of the BB diet before testing object memory at 19 mo postnatally. In experiment 2, rats were tested for object recognition memory at 19 mo and again at 20 mo after 1 mo of maintenance on a 2% BB or control diet. In experiment 1, the control group performed no better than chance, whereas the 1- and 2-mo BB diet groups performed similarly and significantly better than controls. The 2-mo BB-diet group, but not the 1-mo group, maintained its performance over a subsequent month on a standard laboratory diet. In experiment 2, the 19-mo-old rats performed near chance. At 20 mo of age, the rats subsequently maintained on the BB diet significantly increased their object memory scores, whereas the control diet group exhibited a non-significant decline. The change in object memory scores differed significantly between the two diet groups. These results suggest that a considerable degree of age-related object memory decline can be prevented and reversed by brief maintenance on BB diets. Copyright © 2011 Elsevier Inc. All rights reserved.

Category Specificity in Normal Episodic Learning: Applications to Object Recognition and Category-Specific Agnosia

Science.gov (United States)

Bukach, Cindy M.; Bub, Daniel N.; Masson, Michael E. J.; Lindsay, D. Stephen

2004-01-01

Studies of patients with category-specific agnosia (CSA) have given rise to multiple theories of object recognition, most of which assume the existence of a stable, abstract semantic memory system. We applied an episodic view of memory to questions raised by CSA in a series of studies examining normal observers' recall of newly learned attributes…

Noradrenergic activation of the basolateral amygdala modulates the consolidation of object-in-context recognition memory

OpenAIRE

Barsegyan, Areg; McGaugh, James L.; Roozendaal, Benno

2014-01-01

Noradrenergic activation of the basolateral complex of the amygdala (BLA) is well known to enhance the consolidation of long-term memory of highly emotionally arousing training experiences. The present study investigated whether such noradrenergic activation of the BLA also influences the consolidation of object-in-context recognition memory, a low-arousing training task assessing episodic-like memory. Male Sprague-Dawley rats were exposed to two identical objects in one context for either 3 ...

Noradrenergic activation of the basolateral amygdala modulates the consolidation of object-in-context recognition memory

Directory of Open Access Journals (Sweden)

Areg eBarsegyan

2014-05-01

Full Text Available Noradrenergic activation of the basolateral complex of the amygdala (BLA is well known to enhance the consolidation of long-term memory of highly emotionally arousing training experiences. The present study investigated whether such noradrenergic activation of the BLA also influences the consolidation of object-in-context recognition memory, a low-arousing training task assessing episodic-like memory. Male Sprague–Dawley rats were exposed to two identical objects in one context for either 3 or 10 min, immediately followed by exposure to two other identical objects in a distinctly different context. Immediately after the training they received bilateral intra-BLA infusions of norepinephrine (0.3, 1.0 or 3.0 μg or the β-adrenoceptor antagonist propranolol (0.1, 0.3 or 1.0 μg. On the 24-h retention test, rats were placed back into one of the training contexts with one copy of each of the two training objects. Thus, although both objects were familiar, one of the objects had not previously been encountered in this particular test context. Hence, if the animal generated a long-term memory for the association between an object and its context, it would spend significantly more time exploring the object that was not previously experienced in this context. Saline-infused control rats exhibited poor 24-h retention when given 3 min of training and good retention when given 10 min of training. Norepinephrine administered after 3 min of object-in-context training induced a dose-dependent memory enhancement, whereas propranolol administered after 10 min of training produced memory impairment. These findings provide evidence that posttraining noradrenergic activation of the BLA also enhances the consolidation of memory of object-in-context recognition training, enabling accuracy of episodic-like memories.

Divergent short- and long-term effects of acute stress in object recognition memory are mediated by endogenous opioid system activation.

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Nava-Mesa, Mauricio O; Lamprea, Marisol R; Múnera, Alejandro

2013-11-01

Acute stress induces short-term object recognition memory impairment and elicits endogenous opioid system activation. The aim of this study was thus to evaluate whether opiate system activation mediates the acute stress-induced object recognition memory changes. Adult male Wistar rats were trained in an object recognition task designed to test both short- and long-term memory. Subjects were randomly assigned to receive an intraperitoneal injection of saline, 1 mg/kg naltrexone or 3 mg/kg naltrexone, four and a half hours before the sample trial. Five minutes after the injection, half the subjects were submitted to movement restraint during four hours while the other half remained in their home cages. Non-stressed subjects receiving saline (control) performed adequately during the short-term memory test, while stressed subjects receiving saline displayed impaired performance. Naltrexone prevented such deleterious effect, in spite of the fact that it had no intrinsic effect on short-term object recognition memory. Stressed subjects receiving saline and non-stressed subjects receiving naltrexone performed adequately during the long-term memory test; however, control subjects as well as stressed subjects receiving a high dose of naltrexone performed poorly. Control subjects' dissociated performance during both memory tests suggests that the short-term memory test induced a retroactive interference effect mediated through light opioid system activation; such effect was prevented either by low dose naltrexone administration or by strongly activating the opioid system through acute stress. Both short-term memory retrieval impairment and long-term memory improvement observed in stressed subjects may have been mediated through strong opioid system activation, since they were prevented by high dose naltrexone administration. Therefore, the activation of the opioid system plays a dual modulating role in object recognition memory. Copyright © 2013 Elsevier Inc. All rights

Complex method to calculate objective assessments of information systems protection to improve expert assessments reliability

Science.gov (United States)

Abdenov, A. Zh; Trushin, V. A.; Abdenova, G. A.

2018-01-01

The paper considers the questions of filling the relevant SIEM nodes based on calculations of objective assessments in order to improve the reliability of subjective expert assessments. The proposed methodology is necessary for the most accurate security risk assessment of information systems. This technique is also intended for the purpose of establishing real-time operational information protection in the enterprise information systems. Risk calculations are based on objective estimates of the adverse events implementation probabilities, predictions of the damage magnitude from information security violations. Calculations of objective assessments are necessary to increase the reliability of the proposed expert assessments.

Heterozygous Che-1 KO mice show deficiencies in object recognition memory persistence.

Science.gov (United States)

Zalcman, Gisela; Corbi, Nicoletta; Di Certo, Maria Grazia; Mattei, Elisabetta; Federman, Noel; Romano, Arturo

2016-10-06

Transcriptional regulation is a key process in the formation of long-term memories. Che-1 is a protein involved in the regulation of gene transcription that has recently been proved to bind the transcription factor NF-κB, which is known to be involved in many memory-related molecular events. This evidence prompted us to investigate the putative role of Che-1 in memory processes. For this study we newly generated a line of Che-1(+/-) heterozygous mice. Che-1 homozygous KO mouse is lethal during development, but Che-1(+/-) heterozygous mouse is normal in its general anatomical and physiological characteristics. We analyzed the behavioral characteristic and memory performance of Che-1(+/-) mice in two NF-κB dependent types of memory. We found that Che-1(+/-) mice show similar locomotor activity and thigmotactic behavior than wild type (WT) mice in an open field. In a similar way, no differences were found in anxiety-like behavior between Che-1(+/-) and WT mice in an elevated plus maze as well as in fear response in a contextual fear conditioning (CFC) and object exploration in a novel object recognition (NOR) task. No differences were found between WT and Che-1(+/-) mice performance in CFC training and when tested at 24h or 7days after training. Similar performance was found between groups in NOR task, both in training and 24h testing performance. However, we found that object recognition memory persistence at 7days was impaired in Che-1(+/-) heterozygous mice. This is the first evidence showing that Che-1 is involved in memory processes. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Use of iris recognition camera technology for the quantification of corneal opacification in mucopolysaccharidoses.

Science.gov (United States)

Aslam, Tariq Mehmood; Shakir, Savana; Wong, James; Au, Leon; Ashworth, Jane

2012-12-01

Mucopolysaccharidoses (MPS) can cause corneal opacification that is currently difficult to objectively quantify. With newer treatments for MPS comes an increased need for a more objective, valid and reliable index of disease severity for clinical and research use. Clinical evaluation by slit lamp is very subjective and techniques based on colour photography are difficult to standardise. In this article the authors present evidence for the utility of dedicated image analysis algorithms applied to images obtained by a highly sophisticated iris recognition camera that is small, manoeuvrable and adapted to achieve rapid, reliable and standardised objective imaging in a wide variety of patients while minimising artefactual interference in image quality.

Noradrenergic Activation of the Basolateral Amygdala Enhances Object Recognition Memory and Induces Chromatin Remodeling in the Insular Cortex

Directory of Open Access Journals (Sweden)

Hassiba eBeldjoud

2015-04-01

Full Text Available It is well established that arousal-induced memory enhancement requires noradrenergic activation of the basolateral complex of the amygdala (BLA and modulatory influences on information storage processes in its many target regions. While this concept is well accepted, the molecular basis of such BLA effects on neural plasticity changes within other brain regions remains to be elucidated. The present study investigated whether noradrenergic activation of the BLA after object recognition training induces chromatin remodeling through histone post-translational modifications in the insular cortex (IC, a brain region that is importantly involved in object recognition memory. Male Sprague–Dawley rats were trained on an object recognition task, followed immediately by bilateral microinfusions of norepinephrine (1.0 µg or saline administered into the BLA. Saline-treated control rats exhibited poor 24-h retention, whereas norepinephrine treatment induced robust 24-h object recognition memory. Most importantly, this memory-enhancing dose of norepinephrine induced a global reduction in the acetylation levels of histone H3 at lysine 14, H2B and H4 in the IC 1 h later, whereas it had no effect on the phosphorylation of histone H3 at serine 10 or tri-methylation of histone H3 at lysine 27. Norepinephrine administered into the BLA of non-trained control rats did not induce any changes in the histone marks investigated in this study. These findings indicate that noradrenergic activation of the BLA induces training-specific effects on chromatin remodeling mechanisms, and presumably gene transcription, in its target regions, which may contribute to the understanding of the molecular mechanisms of stress and emotional arousal effects on memory consolidation.

Using Markov Chains and Multi-Objective Optimization for Energy-Efficient Context Recognition †

Science.gov (United States)

Janko, Vito

2017-01-01

The recognition of the user’s context with wearable sensing systems is a common problem in ubiquitous computing. However, the typically small battery of such systems often makes continuous recognition impractical. The strain on the battery can be reduced if the sensor setting is adapted to each context. We propose a method that efficiently finds near-optimal sensor settings for each context. It uses Markov chains to simulate the behavior of the system in different configurations and the multi-objective genetic algorithm to find a set of good non-dominated configurations. The method was evaluated on three real-life datasets and found good trade-offs between the system’s energy expenditure and the system’s accuracy. One of the solutions, for example, consumed five-times less energy than the default one, while sacrificing only two percentage points of accuracy. PMID:29286301

A Scientific Workflow Platform for Generic and Scalable Object Recognition on Medical Images

Science.gov (United States)

Möller, Manuel; Tuot, Christopher; Sintek, Michael

In the research project THESEUS MEDICO we aim at a system combining medical image information with semantic background knowledge from ontologies to give clinicians fully cross-modal access to biomedical image repositories. Therefore joint efforts have to be made in more than one dimension: Object detection processes have to be specified in which an abstraction is performed starting from low-level image features across landmark detection utilizing abstract domain knowledge up to high-level object recognition. We propose a system based on a client-server extension of the scientific workflow platform Kepler that assists the collaboration of medical experts and computer scientists during development and parameter learning.

Improving human object recognition performance using video enhancement techniques

Science.gov (United States)

Whitman, Lucy S.; Lewis, Colin; Oakley, John P.

2004-12-01

Atmospheric scattering causes significant degradation in the quality of video images, particularly when imaging over long distances. The principle problem is the reduction in contrast due to scattered light. It is known that when the scattering particles are not too large compared with the imaging wavelength (i.e. Mie scattering) then high spatial resolution information may be contained within a low-contrast image. Unfortunately this information is not easily perceived by a human observer, particularly when using a standard video monitor. A secondary problem is the difficulty of achieving a sharp focus since automatic focus techniques tend to fail in such conditions. Recently several commercial colour video processing systems have become available. These systems use various techniques to improve image quality in low contrast conditions whilst retaining colour content. These systems produce improvements in subjective image quality in some situations, particularly in conditions of haze and light fog. There is also some evidence that video enhancement leads to improved ATR performance when used as a pre-processing stage. Psychological literature indicates that low contrast levels generally lead to a reduction in the performance of human observers in carrying out simple visual tasks. The aim of this paper is to present the results of an empirical study on object recognition in adverse viewing conditions. The chosen visual task was vehicle number plate recognition at long ranges (500 m and beyond). Two different commercial video enhancement systems are evaluated using the same protocol. The results show an increase in effective range with some differences between the different enhancement systems.

Selective attention affects conceptual object priming and recognition: A study with young and older adults

OpenAIRE

Soledad eBallesteros; Julia eMayas

2015-01-01

In the present study, we investigated the effects of selective attention at encoding on conceptual object priming (Experiment 1) and old–new recognition memory (Experiment 2) tasks in young and older adults. The procedures of both experiments included encoding and memory test phases separated by a short delay. At encoding, the picture outlines of two familiar objects, one in blue and the other in green, were presented to the left and to the right of fixation. In Experiment 1, participants wer...

Memory consolidation and expression of object recognition are susceptible to retroactive interference.

Science.gov (United States)

Villar, María Eugenia; Martinez, María Cecilia; Lopes da Cunha, Pamela; Ballarini, Fabricio; Viola, Haydee

2017-02-01

With the aim of analyzing if object recognition long-term memory (OR-LTM) formation is susceptible to retroactive interference (RI), we submitted rats to sequential sample sessions using the same arena but changing the identity of a pair of objects placed in it. Separate groups of animals were tested in the arena in order to evaluate the LTM for these objects. Our results suggest that OR-LTM formation was retroactively interfered within a critical time window by the exploration of a new, but not familiar, object. This RI acted on the consolidation of the object explored in the first sample session because its OR-STM measured 3h after training was not affected, whereas the OR-LTM measured at 24h was impaired. This sample session also impaired the expression of OR memory when it took place before the test. Moreover, local inactivation of the dorsal Hippocampus (Hp) or the medial Prefrontal Cortex (mPFC) previous to the exploration of the second pair of objects impaired their consolidation restoring the LTM for the objects explored in the first session. This data suggests that both brain regions are involved in the processing of OR-memory and also that if those regions are engaged in another process before finishing the first consolidation process its LTM will be impaired by RI. Copyright © 2016 Elsevier Inc. All rights reserved.

Illumination-invariant face recognition with a contrast sensitive silicon retina

Energy Technology Data Exchange (ETDEWEB)

Buhmann, J.M. [Rheinische Friedrich-Wilhelms-Univ., Bonn (Germany). Inst. fuer Informatik II; Lades, M. [Bochum Univ. (Germany). Inst. fuer Neuroinformatik; Eeckman, F. [Lawrence Livermore National Lab., CA (United States)

1993-11-29

Changes in lighting conditions strongly effect the performance and reliability of computer vision systems. We report face recognition results under drastically changing lighting conditions for a computer vision system which concurrently uses a contrast sensitive silicon retina and a conventional, gain controlled CCD camera. For both input devices the face recognition system employs an elastic matching algorithm with wavelet based features to classify unknown faces. To assess the effect of analog on-chip preprocessing by the silicon retina the CCD images have been digitally preprocessed with a bandpass filter to adjust the power spectrum. The silicon retina with its ability to adjust sensitivity increases the recognition rate up to 50 percent. These comparative experiments demonstrate that preprocessing with an analog VLSI silicon retina generates image data enriched with object-constant features.

Real-time object recognition in multidimensional images based on joined extended structural tensor and higher-order tensor decomposition methods

Science.gov (United States)

Cyganek, Boguslaw; Smolka, Bogdan

2015-02-01

In this paper a system for real-time recognition of objects in multidimensional video signals is proposed. Object recognition is done by pattern projection into the tensor subspaces obtained from the factorization of the signal tensors representing the input signal. However, instead of taking only the intensity signal the novelty of this paper is first to build the Extended Structural Tensor representation from the intensity signal that conveys information on signal intensities, as well as on higher-order statistics of the input signals. This way the higher-order input pattern tensors are built from the training samples. Then, the tensor subspaces are built based on the Higher-Order Singular Value Decomposition of the prototype pattern tensors. Finally, recognition relies on measurements of the distance of a test pattern projected into the tensor subspaces obtained from the training tensors. Due to high-dimensionality of the input data, tensor based methods require high memory and computational resources. However, recent achievements in the technology of the multi-core microprocessors and graphic cards allows real-time operation of the multidimensional methods as is shown and analyzed in this paper based on real examples of object detection in digital images.

Infant Visual Recognition Memory

Science.gov (United States)

Rose, Susan A.; Feldman, Judith F.; Jankowski, Jeffery J.

2004-01-01

Visual recognition memory is a robust form of memory that is evident from early infancy, shows pronounced developmental change, and is influenced by many of the same factors that affect adult memory; it is surprisingly resistant to decay and interference. Infant visual recognition memory shows (a) modest reliability, (b) good discriminant…

Modular Adaptive System Based on a Multi-Stage Neural Structure for Recognition of 2D Objects of Discontinuous Production

Directory of Open Access Journals (Sweden)

I. Topalova

2005-03-01

Full Text Available This is a presentation of a new system for invariant recognition of 2D objects with overlapping classes, that can not be effectively recognized with the traditional methods. The translation, scale and partial rotation invariant contour object description is transformed in a DCT spectrum space. The obtained frequency spectrums are decomposed into frequency bands in order to feed different BPG neural nets (NNs. The NNs are structured in three stages - filtering and full rotation invariance; partial recognition; general classification. The designed multi-stage BPG Neural Structure shows very good accuracy and flexibility when tested with 2D objects used in the discontinuous production. The reached speed and the opportunuty for an easy restructuring and reprogramming of the system makes it suitable for application in different applied systems for real time work.

Modular Adaptive System Based on a Multi-Stage Neural Structure for Recognition of 2D Objects of Discontinuous Production

Directory of Open Access Journals (Sweden)

I. Topalova

2008-11-01

Full Text Available This is a presentation of a new system for invariant recognition of 2D objects with overlapping classes, that can not be effectively recognized with the traditional methods. The translation, scale and partial rotation invariant contour object description is transformed in a DCT spectrum space. The obtained frequency spectrums are decomposed into frequency bands in order to feed different BPG neural nets (NNs. The NNs are structured in three stages - filtering and full rotation invariance; partial recognition; general classification. The designed multi-stage BPG Neural Structure shows very good accuracy and flexibility when tested with 2D objects used in the discontinuous production. The reached speed and the opportunuty for an easy restructuring and reprogramming of the system makes it suitable for application in different applied systems for real time work.

Impairment of object recognition memory by maternal bisphenol A exposure is associated with inhibition of Akt and ERK/CREB/BDNF pathway in the male offspring hippocampus.

Science.gov (United States)

Wang, Chong; Li, Zhihui; Han, Haijun; Luo, Guangying; Zhou, Bingrui; Wang, Shaolin; Wang, Jundong

2016-02-03

Bisphenol A (BPA) is a commonly used endocrine-disrupting chemical used as a component of polycarbonates plastics that has potential adverse effects on human health. Exposure to BPA during development has been implicated in memory deficits, but the mechanism of action underlying the effect is not fully understood. In this study, we investigated the effect of maternal exposure to BPA on object recognition memory and the expressions of proteins important for memory, especially focusing on the ERK/CREB/BDNF pathway. Pregnant Sprague-Dawley female rats were orally treated with either vehicle or BPA (0.05, 0.5, 5 or 50 mg/kg BW/day) during days 9-20 of gestation. Male offspring were tested on postnatal day 21 with the object recognition task. Recognition memory was assessed using the object recognition index (index=the time spent exploring the novel object/(the time spent exploring the novel object+the time spent exploring the familiar object)). In the test session performed 90 min after the training session, BPA-exposed male offspring not only spent more time in exploring the familiar object at the highest dose than the control, but also displayed a significantly decreased the object recognition index at the doses of 0.5, 5 and 50 mg/kg BW/day. During the test session performed 24h after the training session, BPA-treated males did not change the time spent exploring the familiar object, but had a decreased object recognition index at 5 and 50 mg/kg BW/day, when compared to control group. These findings indicate that object recognition memory was susceptible to maternal BPA exposure. Western blot analysis of hippocampi from BPA-treated male offspring revealed a decrease in Akt, phospho-Akt, p44/42 MAPK and phospho-p44/42 MAPK protein levels, compared to controls. In addition, BPA significantly inhibited the levels of phosphorylation of CREB and BDNF in the hippocampus. Our results show that maternal BPA exposure may full impair object recognition memory, and that

Three dimensional pattern recognition using feature-based indexing and rule-based search

Science.gov (United States)

Lee, Jae-Kyu

In flexible automated manufacturing, robots can perform routine operations as well as recover from atypical events, provided that process-relevant information is available to the robot controller. Real time vision is among the most versatile sensing tools, yet the reliability of machine-based scene interpretation can be questionable. The effort described here is focused on the development of machine-based vision methods to support autonomous nuclear fuel manufacturing operations in hot cells. This thesis presents a method to efficiently recognize 3D objects from 2D images based on feature-based indexing. Object recognition is the identification of correspondences between parts of a current scene and stored views of known objects, using chains of segments or indexing vectors. To create indexed object models, characteristic model image features are extracted during preprocessing. Feature vectors representing model object contours are acquired from several points of view around each object and stored. Recognition is the process of matching stored views with features or patterns detected in a test scene. Two sets of algorithms were developed, one for preprocessing and indexed database creation, and one for pattern searching and matching during recognition. At recognition time, those indexing vectors with the highest match probability are retrieved from the model image database, using a nearest neighbor search algorithm. The nearest neighbor search predicts the best possible match candidates. Extended searches are guided by a search strategy that employs knowledge-base (KB) selection criteria. The knowledge-based system simplifies the recognition process and minimizes the number of iterations and memory usage. Novel contributions include the use of a feature-based indexing data structure together with a knowledge base. Both components improve the efficiency of the recognition process by improved structuring of the database of object features and reducing data base size

Evaluating music emotion recognition:Lessons from music genre recognition?

OpenAIRE

Sturm, Bob L.

2013-01-01

A fundamental problem with nearly all work in music genre recognition (MGR)is that evaluation lacks validity with respect to the principal goals of MGR. This problem also occurs in the evaluation of music emotion recognition (MER). Standard approaches to evaluation, though easy to implement, do not reliably differentiate between recognizing genre or emotion from music, or by virtue of confounding factors in signals (e.g., equalization). We demonstrate such problems for evaluating an MER syste...

Radar automatic target recognition (ATR) and non-cooperative target recognition (NCTR)

CERN Document Server

Blacknell, David

2013-01-01

The ability to detect and locate targets by day or night, over wide areas, regardless of weather conditions has long made radar a key sensor in many military and civil applications. However, the ability to automatically and reliably distinguish different targets represents a difficult challenge. Radar Automatic Target Recognition (ATR) and Non-Cooperative Target Recognition (NCTR) captures material presented in the NATO SET-172 lecture series to provide an overview of the state-of-the-art and continuing challenges of radar target recognition. Topics covered include the problem as applied to th

Reliability database development for use with an object-oriented fault tree evaluation program

Science.gov (United States)

Heger, A. Sharif; Harringtton, Robert J.; Koen, Billy V.; Patterson-Hine, F. Ann

1989-01-01

A description is given of the development of a fault-tree analysis method using object-oriented programming. In addition, the authors discuss the programs that have been developed or are under development to connect a fault-tree analysis routine to a reliability database. To assess the performance of the routines, a relational database simulating one of the nuclear power industry databases has been constructed. For a realistic assessment of the results of this project, the use of one of existing nuclear power reliability databases is planned.

Optical Pattern Recognition

Science.gov (United States)

Yu, Francis T. S.; Jutamulia, Suganda

2008-10-01

Contributors; Preface; 1. Pattern recognition with optics Francis T. S. Yu and Don A. Gregory; 2. Hybrid neural networks for nonlinear pattern recognition Taiwei Lu; 3. Wavelets, optics, and pattern recognition Yao Li and Yunglong Sheng; 4. Applications of the fractional Fourier transform to optical pattern recognition David Mendlovic, Zeev Zalesky and Haldum M. Oxaktas; 5. Optical implementation of mathematical morphology Tien-Hsin Chao; 6. Nonlinear optical correlators with improved discrimination capability for object location and recognition Leonid P. Yaroslavsky; 7. Distortion-invariant quadratic filters Gregory Gheen; 8. Composite filter synthesis as applied to pattern recognition Shizhou Yin and Guowen Lu; 9. Iterative procedures in electro-optical pattern recognition Joseph Shamir; 10. Optoelectronic hybrid system for three-dimensional object pattern recognition Guoguang Mu, Mingzhe Lu and Ying Sun; 11. Applications of photrefractive devices in optical pattern recognition Ziangyang Yang; 12. Optical pattern recognition with microlasers Eung-Gi Paek; 13. Optical properties and applications of bacteriorhodopsin Q. Wang Song and Yu-He Zhang; 14. Liquid-crystal spatial light modulators Aris Tanone and Suganda Jutamulia; 15. Representations of fully complex functions on real-time spatial light modulators Robert W. Cohn and Laurence G. Hassbrook; Index.

Reliable and Accurate Release of Micro-Sized Objects with a Gripper that Uses the Capillary-Force Method

Directory of Open Access Journals (Sweden)

Suzana Uran

2017-06-01

Full Text Available There have been recent developments in grippers that are based on capillary force and condensed water droplets. These are used for manipulating micro-sized objects. Recently, one-finger grippers have been produced that are able to reliably grip using the capillary force. To release objects, either the van der Waals, gravitational or inertial-forces method is used. This article presents methods for reliably gripping and releasing micro-objects using the capillary force. The moisture from the surrounding air is condensed into a thin layer of water on the contact surfaces of the objects. From the thin layer of water, a water meniscus between the micro-sized object, the gripper and the releasing surface is created. Consequently, the water meniscus between the object and the releasing surface produces a high enough capillary force to release the micro-sized object from the tip of the one-finger gripper. In this case, either polystyrene, glass beads with diameters between 5–60 µm, or irregularly shaped dust particles of similar sizes were used. 3D structures made up of micro-sized objects could be constructed using this method. This method is reliable for releasing during assembly and also for gripping, when the objects are removed from the top of the 3D structure—the so-called “disassembling gripping” process. The accuracy of the release was lower than 0.5 µm.

Visual object recognition and tracking

Science.gov (United States)

Chang, Chu-Yin (Inventor); English, James D. (Inventor); Tardella, Neil M. (Inventor)

2010-01-01

This invention describes a method for identifying and tracking an object from two-dimensional data pictorially representing said object by an object-tracking system through processing said two-dimensional data using at least one tracker-identifier belonging to the object-tracking system for providing an output signal containing: a) a type of the object, and/or b) a position or an orientation of the object in three-dimensions, and/or c) an articulation or a shape change of said object in said three dimensions.

Activity and function recognition for moving and static objects in urban environments from wide-area persistent surveillance inputs

Science.gov (United States)

Levchuk, Georgiy; Bobick, Aaron; Jones, Eric

2010-04-01

In this paper, we describe results from experimental analysis of a model designed to recognize activities and functions of moving and static objects from low-resolution wide-area video inputs. Our model is based on representing the activities and functions using three variables: (i) time; (ii) space; and (iii) structures. The activity and function recognition is achieved by imposing lexical, syntactic, and semantic constraints on the lower-level event sequences. In the reported research, we have evaluated the utility and sensitivity of several algorithms derived from natural language processing and pattern recognition domains. We achieved high recognition accuracy for a wide range of activity and function types in the experiments using Electro-Optical (EO) imagery collected by Wide Area Airborne Surveillance (WAAS) platform.

Impulsivity and novel object recognition test of rat model for vascular cognitive impairment after antipsychotics treatment

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Ronny T Wirasto

2016-12-01

Full Text Available ABSTRACT Vascular cognitive impairment (VCI is a common condition in which no standard treatment has been approved. VCI is often accompanied by behavioral problems which require psychiatric interventions. The common therapeutic agent used for the acute management is antipsychotic injections. Current findings showed that atypical antipsychotic possess better safety profile for treating behavioral problems related to VCI compared to typical antipsychotic. In this study, we induced VCI in Sprague Dawley rats between 6-8 weeks old using bilateral carotid communist artery occlusion technique. The subjects were divided into 4 treatment groups: sham, olanzapine, haloperidol, and risperidone groups. Subjects received intramuscular injections of subsequent drugs for 3 days post VCI induction. Impulsive behavior and object recognition were examined using cliff jumping test and novel object recognition test. The analyses results showed that impulsive behavior was lower in the olanzapine and haloperidol groups compared to sham group, although it was not statistically significant (p = 0.651. The results also showed that there were no significant differences in the time spent exploring old and novel objects in all groups (p = 0.945;0.637 respectively. In conclusion, antipsychotic injection might not be effective to control impulsive behavior post VCI induction.

Excess influx of Zn(2+) into dentate granule cells affects object recognition memory via attenuated LTP.

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Suzuki, Miki; Fujise, Yuki; Tsuchiya, Yuka; Tamano, Haruna; Takeda, Atsushi

2015-08-01

The influx of extracellular Zn(2+) into dentate granule cells is nonessential for dentate gyrus long-term potentiation (LTP) and the physiological significance of extracellular Zn(2+) dynamics is unknown in the dentate gyrus. Excess increase in extracellular Zn(2+) in the hippocampal CA1, which is induced with excitation of zincergic neurons, induces memory deficit via excess influx of Zn(2+) into CA1 pyramidal cells. In the present study, it was examined whether extracellular Zn(2+) induces object recognition memory deficit via excess influx of Zn(2+) into dentate granule cells. KCl (100 mM, 2 µl) was locally injected into the dentate gyrus. The increase in intracellular Zn(2+) in dentate granule cells induced with high K(+) was blocked by co-injection of CaEDTA and CNQX, an extracellular Zn(2+) chelator and an AMPA receptor antagonist, respectively, suggesting that high K(+) increases the influx of Zn(2+) into dentate granule cells via AMPA receptor activation. Dentate gyrus LTP induction was attenuated 1 h after KCl injection into the dentate gyrus and also attenuated when KCl was injected 5 min after the induction. Memory deficit was induced when training of object recognition test was performed 1 h after KCl injection into the dentate gyrus and also induced when KCl was injected 5 min after the training. High K(+)-induced impairments of LTP and memory were rescued by co-injection of CaEDTA. These results indicate that excess influx of Zn(2+) into dentate granule cells via AMPA receptor activation affects object recognition memory via attenuated LTP induction. Even in the dentate gyrus where is scarcely innervated by zincergic neurons, it is likely that extracellular Zn(2+) homeostasis is strictly regulated for cognition. Copyright © 2015 Elsevier Ltd. All rights reserved.

Genetic Mapping in Mice Reveals the Involvement of Pcdh9 in Long-Term Social and Object Recognition and Sensorimotor Development.

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Bruining, Hilgo; Matsui, Asuka; Oguro-Ando, Asami; Kahn, René S; Van't Spijker, Heleen M; Akkermans, Guus; Stiedl, Oliver; van Engeland, Herman; Koopmans, Bastijn; van Lith, Hein A; Oppelaar, Hugo; Tieland, Liselotte; Nonkes, Lourens J; Yagi, Takeshi; Kaneko, Ryosuke; Burbach, J Peter H; Yamamoto, Nobuhiko; Kas, Martien J

2015-10-01

Quantitative genetic analysis of basic mouse behaviors is a powerful tool to identify novel genetic phenotypes contributing to neurobehavioral disorders. Here, we analyzed genetic contributions to single-trial, long-term social and nonsocial recognition and subsequently studied the functional impact of an identified candidate gene on behavioral development. Genetic mapping of single-trial social recognition was performed in chromosome substitution strains, a sophisticated tool for detecting quantitative trait loci (QTL) of complex traits. Follow-up occurred by generating and testing knockout (KO) mice of a selected QTL candidate gene. Functional characterization of these mice was performed through behavioral and neurological assessments across developmental stages and analyses of gene expression and brain morphology. Chromosome substitution strain 14 mapping studies revealed an overlapping QTL related to long-term social and object recognition harboring Pcdh9, a cell-adhesion gene previously associated with autism spectrum disorder. Specific long-term social and object recognition deficits were confirmed in homozygous (KO) Pcdh9-deficient mice, while heterozygous mice only showed long-term social recognition impairment. The recognition deficits in KO mice were not associated with alterations in perception, multi-trial discrimination learning, sociability, behavioral flexibility, or fear memory. Rather, KO mice showed additional impairments in sensorimotor development reflected by early touch-evoked biting, rotarod performance, and sensory gating deficits. This profile emerged with structural changes in deep layers of sensory cortices, where Pcdh9 is selectively expressed. This behavior-to-gene study implicates Pcdh9 in cognitive functions required for long-term social and nonsocial recognition. This role is supported by the involvement of Pcdh9 in sensory cortex development and sensorimotor phenotypes. Copyright © 2015 Society of Biological Psychiatry. Published

Insect brains use image interpolation mechanisms to recognise rotated objects.

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Adrian G Dyer

Full Text Available Recognising complex three-dimensional objects presents significant challenges to visual systems when these objects are rotated in depth. The image processing requirements for reliable individual recognition under these circumstances are computationally intensive since local features and their spatial relationships may significantly change as an object is rotated in the horizontal plane. Visual experience is known to be important in primate brains learning to recognise rotated objects, but currently it is unknown how animals with comparatively simple brains deal with the problem of reliably recognising objects when seen from different viewpoints. We show that the miniature brain of honeybees initially demonstrate a low tolerance for novel views of complex shapes (e.g. human faces, but can learn to recognise novel views of stimuli by interpolating between or 'averaging' views they have experienced. The finding that visual experience is also important for bees has important implications for understanding how three dimensional biologically relevant objects like flowers are recognised in complex environments, and for how machine vision might be taught to solve related visual problems.

Reader error, object recognition, and visual search

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Kundel, Harold L.

2004-05-01

Small abnormalities such as hairline fractures, lung nodules and breast tumors are missed by competent radiologists with sufficient frequency to make them a matter of concern to the medical community; not only because they lead to litigation but also because they delay patient care. It is very easy to attribute misses to incompetence or inattention. To do so may be placing an unjustified stigma on the radiologists involved and may allow other radiologists to continue a false optimism that it can never happen to them. This review presents some of the fundamentals of visual system function that are relevant to understanding the search for and the recognition of small targets embedded in complicated but meaningful backgrounds like chests and mammograms. It presents a model for visual search that postulates a pre-attentive global analysis of the retinal image followed by foveal checking fixations and eventually discovery scanning. The model will be used to differentiate errors of search, recognition and decision making. The implications for computer aided diagnosis and for functional workstation design are discussed.

Now you see it, now you don’t: The context dependent nature of category-effects in visual object recognition

DEFF Research Database (Denmark)

Gerlach, Christian; Toft, Kristian Olesen

2011-01-01

In two experiments, we test predictions regarding processing advantages/disadvantages for natural objects and artefacts in visual object recognition. Varying three important parameters*degree of perceptual differentiation, stimulus format, and stimulus exposure duration*we show how different......-effects are products of common operations which are differentially affected by the structural similarity among objects (with natural objects being more structurally similar than artefacts). The potentially most important aspect of the present study is the demonstration that category-effects are very context dependent...

Conversion of short-term to long-term memory in the novel object recognition paradigm.

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Moore, Shannon J; Deshpande, Kaivalya; Stinnett, Gwen S; Seasholtz, Audrey F; Murphy, Geoffrey G

2013-10-01

It is well-known that stress can significantly impact learning; however, whether this effect facilitates or impairs the resultant memory depends on the characteristics of the stressor. Investigation of these dynamics can be confounded by the role of the stressor in motivating performance in a task. Positing a cohesive model of the effect of stress on learning and memory necessitates elucidating the consequences of stressful stimuli independently from task-specific functions. Therefore, the goal of this study was to examine the effect of manipulating a task-independent stressor (elevated light level) on short-term and long-term memory in the novel object recognition paradigm. Short-term memory was elicited in both low light and high light conditions, but long-term memory specifically required high light conditions during the acquisition phase (familiarization trial) and was independent of the light level during retrieval (test trial). Additionally, long-term memory appeared to be independent of stress-mediated glucocorticoid release, as both low and high light produced similar levels of plasma corticosterone, which further did not correlate with subsequent memory performance. Finally, both short-term and long-term memory showed no savings between repeated experiments suggesting that this novel object recognition paradigm may be useful for longitudinal studies, particularly when investigating treatments to stabilize or enhance weak memories in neurodegenerative diseases or during age-related cognitive decline. Copyright © 2013 Elsevier Inc. All rights reserved.

Random-Profiles-Based 3D Face Recognition System

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Joongrock Kim

2014-03-01

Full Text Available In this paper, a noble nonintrusive three-dimensional (3D face modeling system for random-profile-based 3D face recognition is presented. Although recent two-dimensional (2D face recognition systems can achieve a reliable recognition rate under certain conditions, their performance is limited by internal and external changes, such as illumination and pose variation. To address these issues, 3D face recognition, which uses 3D face data, has recently received much attention. However, the performance of 3D face recognition highly depends on the precision of acquired 3D face data, while also requiring more computational power and storage capacity than 2D face recognition systems. In this paper, we present a developed nonintrusive 3D face modeling system composed of a stereo vision system and an invisible near-infrared line laser, which can be directly applied to profile-based 3D face recognition. We further propose a novel random-profile-based 3D face recognition method that is memory-efficient and pose-invariant. The experimental results demonstrate that the reconstructed 3D face data consists of more than 50 k 3D point clouds and a reliable recognition rate against pose variation.

Constant Light Desynchronizes Olfactory versus Object and Visuospatial Recognition Memory Performance.

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Tam, Shu K E; Hasan, Sibah; Choi, Harry M C; Brown, Laurence A; Jagannath, Aarti; Hughes, Steven; Hankins, Mark W; Foster, Russell G; Vyazovskiy, Vladyslav V; Bannerman, David M; Peirson, Stuart N

2017-03-29

Circadian rhythms optimize physiology and behavior to the varying demands of the 24 h day. The master circadian clock is located in the suprachiasmatic nuclei (SCN) of the hypothalamus and it regulates circadian oscillators in tissues throughout the body to prevent internal desynchrony. Here, we demonstrate for the first time that, under standard 12 h:12 h light/dark (LD) cycles, object, visuospatial, and olfactory recognition performance in C57BL/6J mice is consistently better at midday relative to midnight. However, under repeated exposure to constant light ( r LL), recognition performance becomes desynchronized, with object and visuospatial performance better at subjective midday and olfactory performance better at subjective midnight. This desynchrony in behavioral performance is mirrored by changes in expression of the canonical clock genes Period1 and Period2 ( Per1 and Per2 ), as well as the immediate-early gene Fos in the SCN, dorsal hippocampus, and olfactory bulb. Under r LL, rhythmic Per1 and Fos expression is attenuated in the SCN. In contrast, hippocampal gene expression remains rhythmic, mirroring object and visuospatial performance. Strikingly, Per1 and Fos expression in the olfactory bulb is reversed, mirroring the inverted olfactory performance. Temporal desynchrony among these regions does not result in arrhythmicity because core body temperature and exploratory activity rhythms persist under r LL. Our data provide the first demonstration that abnormal lighting conditions can give rise to temporal desynchrony between autonomous circadian oscillators in different regions, with different consequences for performance across different sensory domains. Such a dispersed network of dissociable circadian oscillators may provide greater flexibility when faced with conflicting environmental signals. SIGNIFICANCE STATEMENT A master circadian clock in the suprachiasmatic nuclei (SCN) of the hypothalamus regulates physiology and behavior across the 24 h day by

Constant Light Desynchronizes Olfactory versus Object and Visuospatial Recognition Memory Performance

Science.gov (United States)

Tam, Shu K.E.; Hasan, Sibah; Brown, Laurence A.; Jagannath, Aarti; Hankins, Mark W.; Foster, Russell G.; Vyazovskiy, Vladyslav V.

2017-01-01

Circadian rhythms optimize physiology and behavior to the varying demands of the 24 h day. The master circadian clock is located in the suprachiasmatic nuclei (SCN) of the hypothalamus and it regulates circadian oscillators in tissues throughout the body to prevent internal desynchrony. Here, we demonstrate for the first time that, under standard 12 h:12 h light/dark (LD) cycles, object, visuospatial, and olfactory recognition performance in C57BL/6J mice is consistently better at midday relative to midnight. However, under repeated exposure to constant light (rLL), recognition performance becomes desynchronized, with object and visuospatial performance better at subjective midday and olfactory performance better at subjective midnight. This desynchrony in behavioral performance is mirrored by changes in expression of the canonical clock genes Period1 and Period2 (Per1 and Per2), as well as the immediate-early gene Fos in the SCN, dorsal hippocampus, and olfactory bulb. Under rLL, rhythmic Per1 and Fos expression is attenuated in the SCN. In contrast, hippocampal gene expression remains rhythmic, mirroring object and visuospatial performance. Strikingly, Per1 and Fos expression in the olfactory bulb is reversed, mirroring the inverted olfactory performance. Temporal desynchrony among these regions does not result in arrhythmicity because core body temperature and exploratory activity rhythms persist under rLL. Our data provide the first demonstration that abnormal lighting conditions can give rise to temporal desynchrony between autonomous circadian oscillators in different regions, with different consequences for performance across different sensory domains. Such a dispersed network of dissociable circadian oscillators may provide greater flexibility when faced with conflicting environmental signals. SIGNIFICANCE STATEMENT A master circadian clock in the suprachiasmatic nuclei (SCN) of the hypothalamus regulates physiology and behavior across the 24 h day by

A two-stage approach for multi-objective decision making with applications to system reliability optimization

International Nuclear Information System (INIS)

Li Zhaojun; Liao Haitao; Coit, David W.

2009-01-01

This paper proposes a two-stage approach for solving multi-objective system reliability optimization problems. In this approach, a Pareto optimal solution set is initially identified at the first stage by applying a multiple objective evolutionary algorithm (MOEA). Quite often there are a large number of Pareto optimal solutions, and it is difficult, if not impossible, to effectively choose the representative solutions for the overall problem. To overcome this challenge, an integrated multiple objective selection optimization (MOSO) method is utilized at the second stage. Specifically, a self-organizing map (SOM), with the capability of preserving the topology of the data, is applied first to classify those Pareto optimal solutions into several clusters with similar properties. Then, within each cluster, the data envelopment analysis (DEA) is performed, by comparing the relative efficiency of those solutions, to determine the final representative solutions for the overall problem. Through this sequential solution identification and pruning process, the final recommended solutions to the multi-objective system reliability optimization problem can be easily determined in a more systematic and meaningful way.

A Temporally Distinct Role for Group I and Group II Metabotropic Glutamate Receptors in Object Recognition Memory

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Brown, Malcolm Watson; Warburton, Elizabeth Clea; Barker, Gareth Robert Isaac; Bashir, Zafar Iqbal

2006-01-01

Recognition memory, involving the ability to discriminate between a novel and familiar object, depends on the integrity of the perirhinal cortex (PRH). Glutamate, the main excitatory neurotransmitter in the cortex, is essential for many types of memory processes. Of the subtypes of glutamate receptor, metabotropic receptors (mGluRs) have received…

Reliable software systems via chains of object models with provably correct behavior

International Nuclear Information System (INIS)

Yakhnis, A.; Yakhnis, V.

1996-01-01

This work addresses specification and design of reliable safety-critical systems, such as nuclear reactor control systems. Reliability concerns are addressed in complimentary fashion by different fields. Reliability engineers build software reliability models, etc. Safety engineers focus on prevention of potential harmful effects of systems on environment. Software/hardware correctness engineers focus on production of reliable systems on the basis of mathematical proofs. The authors think that correctness may be a crucial guiding issue in the development of reliable safety-critical systems. However, purely formal approaches are not adequate for the task, because they neglect the connection with the informal customer requirements. They alleviate that as follows. First, on the basis of the requirements, they build a model of the system interactions with the environment, where the system is viewed as a black box. They will provide foundations for automated tools which will (a) demonstrate to the customer that all of the scenarios of system behavior are presented in the model, (b) uncover scenarios not present in the requirements, and (c) uncover inconsistent scenarios. The developers will work with the customer until the black box model will not possess scenarios (b) and (c) above. Second, the authors will build a chain of several increasingly detailed models, where the first model is the black box model and the last model serves to automatically generated proved executable code. The behavior of each model will be proved to conform to the behavior of the previous one. They build each model as a cluster of interactive concurrent objects, thus they allow both top-down and bottom-up development

Mid-level perceptual features distinguish objects of different real-world sizes.

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Long, Bria; Konkle, Talia; Cohen, Michael A; Alvarez, George A

2016-01-01

Understanding how perceptual and conceptual representations are connected is a fundamental goal of cognitive science. Here, we focus on a broad conceptual distinction that constrains how we interact with objects--real-world size. Although there appear to be clear perceptual correlates for basic-level categories (apples look like other apples, oranges look like other oranges), the perceptual correlates of broader categorical distinctions are largely unexplored, i.e., do small objects look like other small objects? Because there are many kinds of small objects (e.g., cups, keys), there may be no reliable perceptual features that distinguish them from big objects (e.g., cars, tables). Contrary to this intuition, we demonstrated that big and small objects have reliable perceptual differences that can be extracted by early stages of visual processing. In a series of visual search studies, participants found target objects faster when the distractor objects differed in real-world size. These results held when we broadly sampled big and small objects, when we controlled for low-level features and image statistics, and when we reduced objects to texforms--unrecognizable textures that loosely preserve an object's form. However, this effect was absent when we used more basic textures. These results demonstrate that big and small objects have reliably different mid-level perceptual features, and suggest that early perceptual information about broad-category membership may influence downstream object perception, recognition, and categorization processes. (c) 2015 APA, all rights reserved).

Advances in biometrics for secure human authentication and recognition

CERN Document Server

Kisku, Dakshina Ranjan; Sing, Jamuna Kanta

2013-01-01

GENERAL BIOMETRICSSecurity and Reliability Assessment for Biometric Systems; Gayatri MirajkarReview of Human Recognition Based on Retinal Images; Amin DehghaniADVANCED TOPICS IN BIOMETRICSVisual Speech as Behavioral Biometric; Preety Singh, Vijay Laxmi, and Manoj Singh GaurHuman Gait Signature for Biometric Authentication; Vijay JohnHand-Based Biometric for Personal Identification Using Correlation Filter Classifier; Mohammed Saigaa , Abdallah Meraoumia , Salim Chitroub, and Ahmed BouridaneOn Deciding the Dynamic Periocular Boundary for Human Recognition; Sambit Bakshi , Pankaj Kumar Sa, and Banshidhar MajhiRetention of Electrocardiogram Features Insignificantly Devalorized as an Effect of Watermarking for a Multimodal Biometric Authentication System; Nilanjan Dey, Bijurika Nandi, Poulami Das, Achintya Das, and Sheli Sinha ChaudhuriFacial Feature Point Extraction for Object Identification Using Discrete Contourlet Transform and Principal Component Analysis; N. G. Chitaliya and A. I. TrivediCASE STUDIES AND LA...

Effects of heavy particle irradiation and diet on object recognition memory in rats

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Rabin, Bernard M.; Carrihill-Knoll, Kirsty; Hinchman, Marie; Shukitt-Hale, Barbara; Joseph, James A.; Foster, Brian C.

2009-04-01

On long-duration missions to other planets astronauts will be exposed to types and doses of radiation that are not experienced in low earth orbit. Previous research using a ground-based model for exposure to cosmic rays has shown that exposure to heavy particles, such as 56Fe, disrupts spatial learning and memory measured using the Morris water maze. Maintaining rats on diets containing antioxidant phytochemicals for 2 weeks prior to irradiation ameliorated this deficit. The present experiments were designed to determine: (1) the generality of the particle-induced disruption of memory by examining the effects of exposure to 56Fe particles on object recognition memory; and (2) whether maintaining rats on these antioxidant diets for 2 weeks prior to irradiation would also ameliorate any potential deficit. The results showed that exposure to low doses of 56Fe particles does disrupt recognition memory and that maintaining rats on antioxidant diets containing blueberry and strawberry extract for only 2 weeks was effective in ameliorating the disruptive effects of irradiation. The results are discussed in terms of the mechanisms by which exposure to these particles may produce effects on neurocognitive performance.

Face Perception and Test Reliabilities in Congenital Prosopagnosia in Seven Tests

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Janina Esins

2016-01-01

Full Text Available Congenital prosopagnosia, the innate impairment in recognizing faces, is a very heterogeneous disorder with different phenotypical manifestations. To investigate the nature of prosopagnosia in more detail, we tested 16 prosopagnosics and 21 controls with an extended test battery addressing various aspects of face recognition. Our results show that prosopagnosics exhibited significant impairments in several face recognition tasks: impaired holistic processing (they were tested amongst others with the Cambridge Face Memory Test (CFMT as well as reduced processing of configural information of faces. This test battery also revealed some new findings. While controls recognized moving faces better than static faces, prosopagnosics did not exhibit this effect. Furthermore, prosopagnosics had significantly impaired gender recognition—which is shown on a groupwise level for the first time in our study. There was no difference between groups in the automatic extraction of face identity information or in object recognition as tested with the Cambridge Car Memory Test. In addition, a methodological analysis of the tests revealed reduced reliability for holistic face processing tests in prosopagnosics. To our knowledge, this is the first study to show that prosopagnosics showed a significantly reduced reliability coefficient (Cronbach’s alpha in the CFMT compared to the controls. We suggest that compensatory strategies employed by the prosopagnosics might be the cause for the vast variety of response patterns revealed by the reduced test reliability. This finding raises the question whether classical face tests measure the same perceptual processes in controls and prosopagnosics.

A neuromorphic architecture for object recognition and motion anticipation using burst-STDP.

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Andrew Nere

Full Text Available In this work we investigate the possibilities offered by a minimal framework of artificial spiking neurons to be deployed in silico. Here we introduce a hierarchical network architecture of spiking neurons which learns to recognize moving objects in a visual environment and determine the correct motor output for each object. These tasks are learned through both supervised and unsupervised spike timing dependent plasticity (STDP. STDP is responsible for the strengthening (or weakening of synapses in relation to pre- and post-synaptic spike times and has been described as a Hebbian paradigm taking place both in vitro and in vivo. We utilize a variation of STDP learning, called burst-STDP, which is based on the notion that, since spikes are expensive in terms of energy consumption, then strong bursting activity carries more information than single (sparse spikes. Furthermore, this learning algorithm takes advantage of homeostatic renormalization, which has been hypothesized to promote memory consolidation during NREM sleep. Using this learning rule, we design a spiking neural network architecture capable of object recognition, motion detection, attention towards important objects, and motor control outputs. We demonstrate the abilities of our design in a simple environment with distractor objects, multiple objects moving concurrently, and in the presence of noise. Most importantly, we show how this neural network is capable of performing these tasks using a simple leaky-integrate-and-fire (LIF neuron model with binary synapses, making it fully compatible with state-of-the-art digital neuromorphic hardware designs. As such, the building blocks and learning rules presented in this paper appear promising for scalable fully neuromorphic systems to be implemented in hardware chips.

An objective spinal motion imaging assessment (OSMIA): reliability, accuracy and exposure data.

OpenAIRE

Breen, Alan C.; Muggleton, J.M.; Mellor, F.E.

2006-01-01

Abstract Background Minimally-invasive measurement of continuous inter-vertebral motion in clinical settings is difficult to achieve. This paper describes the reliability, validity and radiation exposure levels in a new Objective Spinal Motion Imaging Assessment system (OSMIA) based on low-dose fluoroscopy and image processing. Methods Fluoroscopic sequences in coronal and sagittal planes were obtained from 2 calibration models using dry lumbar vertebrae, plus the lumbar spines of 30 asymptom...

Role of the Anterior Cingulate Cortex in the Retrieval of Novel Object Recognition Memory after a Long Delay

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Pezze, Marie A.; Marshall, Hayley J.; Fone, Kevin C. F.; Cassaday, Helen J.

2017-01-01

Previous in vivo electrophysiological studies suggest that the anterior cingulate cortex (ACgx) is an important substrate of novel object recognition (NOR) memory. However, intervention studies are needed to confirm this conclusion and permanent lesion studies cannot distinguish effects on encoding and retrieval. The interval between encoding and…

The effect of Wi-Fi electromagnetic waves in unimodal and multimodal object recognition tasks in male rats.

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Hassanshahi, Amin; Shafeie, Seyed Ali; Fatemi, Iman; Hassanshahi, Elham; Allahtavakoli, Mohammad; Shabani, Mohammad; Roohbakhsh, Ali; Shamsizadeh, Ali

2017-06-01

Wireless internet (Wi-Fi) electromagnetic waves (2.45 GHz) have widespread usage almost everywhere, especially in our homes. Considering the recent reports about some hazardous effects of Wi-Fi signals on the nervous system, this study aimed to investigate the effect of 2.4 GHz Wi-Fi radiation on multisensory integration in rats. This experimental study was done on 80 male Wistar rats that were allocated into exposure and sham groups. Wi-Fi exposure to 2.4 GHz microwaves [in Service Set Identifier mode (23.6 dBm and 3% for power and duty cycle, respectively)] was done for 30 days (12 h/day). Cross-modal visual-tactile object recognition (CMOR) task was performed by four variations of spontaneous object recognition (SOR) test including standard SOR, tactile SOR, visual SOR, and CMOR tests. A discrimination ratio was calculated to assess the preference of animal to the novel object. The expression levels of M1 and GAT1 mRNA in the hippocampus were assessed by quantitative real-time RT-PCR. Results demonstrated that rats in Wi-Fi exposure groups could not discriminate significantly between the novel and familiar objects in any of the standard SOR, tactile SOR, visual SOR, and CMOR tests. The expression of M1 receptors increased following Wi-Fi exposure. In conclusion, results of this study showed that chronic exposure to Wi-Fi electromagnetic waves might impair both unimodal and cross-modal encoding of information.

The influence of object and background color manipulations on the electrophysiological indices of recognition memory.

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Ecker, Ullrich K H; Zimmer, Hubert D; Groh-Bordin, Christian

2007-12-14

In a recognition memory experiment, the claim was tested that intrinsic object features contribute to familiarity, whereas extrinsic context features do not. We used the study-test manipulation of color to investigate the perceptual specificity of ERP old-new effects associated with familiarity and recollection. Color was either an intrinsic surface feature of the object or a feature of the surrounding context (a frame encasing the object); thus, the same feature was manipulated across intrinsic/extrinsic conditions. Subjects performed a threefold (same color/different color/new object) decision, making feature information task-relevant. Results suggest that the intrinsic manipulation of color affected the mid-frontal old-new effect associated with familiarity, while this effect was not influenced by extrinsic manipulation. This ERP pattern could not be explained by basic behavioral performance differences. It is concluded that familiarity can be perceptually specific with regard to intrinsic information belonging to the object. The putative electrophysiological signature of recollection - a late parietal old-new effect - was not present in the data, and reasons for this null effect are discussed.

Chronic cannabidiol treatment improves social and object recognition in double transgenic APPswe/PS1∆E9 mice.

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Cheng, David; Low, Jac Kee; Logge, Warren; Garner, Brett; Karl, Tim

2014-08-01

Patients suffering from Alzheimer's disease (AD) exhibit a decline in cognitive abilities including an inability to recognise familiar faces. Hallmark pathological changes in AD include the aggregation of amyloid-β (Aβ), tau protein hyperphosphorylation as well as pronounced neurodegeneration, neuroinflammation, neurotoxicity and oxidative damage. The non-psychoactive phytocannabinoid cannabidiol (CBD) exerts neuroprotective, anti-oxidant and anti-inflammatory effects and promotes neurogenesis. CBD also reverses Aβ-induced spatial memory deficits in rodents. Thus we determined the therapeutic-like effects of chronic CBD treatment (20 mg/kg, daily intraperitoneal injections for 3 weeks) on the APPswe/PS1∆E9 (APPxPS1) transgenic mouse model for AD in a number of cognitive tests, including the social preference test, the novel object recognition task and the fear conditioning paradigm. We also analysed the impact of CBD on anxiety behaviours in the elevated plus maze. Vehicle-treated APPxPS1 mice demonstrated impairments in social recognition and novel object recognition compared to wild type-like mice. Chronic CBD treatment reversed these cognitive deficits in APPxPS1 mice without affecting anxiety-related behaviours. This is the first study to investigate the effect of chronic CBD treatment on cognition in an AD transgenic mouse model. Our findings suggest that CBD may have therapeutic potential for specific cognitive impairments associated with AD.

Risperidone reverses the spatial object recognition impairment and hippocampal BDNF-TrkB signalling system alterations induced by acute MK-801 treatment

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Chen, Guangdong; Lin, Xiaodong; Li, Gongying; Jiang, Diego; Lib, Zhiruo; Jiang, Ronghuan; Zhuo, Chuanjun

2017-01-01

The aim of the present study was to investigate the effects of a commonly-used atypical antipsychotic, risperidone, on alterations in spatial learning and in the hippocampal brain-derived neurotrophic factor (BDNF)-tyrosine receptor kinase B (TrkB) signalling system caused by acute dizocilpine maleate (MK-801) treatment. In experiment 1, adult male Sprague-Dawley rats subjected to acute treatment of either low-dose MK801 (0.1 mg/kg) or normal saline (vehicle) were tested for spatial object recognition and hippocampal expression levels of BDNF, TrkB and the phophorylation of TrkB (p-TrkB). We found that compared to the vehicle, MK-801 treatment impaired spatial object recognition of animals and downregulated the expression levels of p-TrkB. In experiment 2, MK-801- or vehicle-treated animals were further injected with risperidone (0.1 mg/kg) or vehicle before behavioural testing and sacrifice. Of note, we found that risperidone successfully reversed the deleterious effects of MK-801 on spatial object recognition and upregulated the hippocampal BDNF-TrkB signalling system. Collectively, the findings suggest that cognitive deficits from acute N-methyl-D-aspartate receptor blockade may be associated with the hypofunction of hippocampal BDNF-TrkB signalling system and that risperidone was able to reverse these alterations. PMID:28451387

A multi-objective reliable programming model for disruption in supply chain

Directory of Open Access Journals (Sweden)

Emran Mohammadi

2013-05-01

Full Text Available One of the primary concerns on supply chain management is to handle risk components, properly. There are various reasons for having risk in supply chain such as natural disasters, unexpected incidents, etc. When a series of facilities are built and deployed, one or a number of them could probably fail at any time due to bad weather conditions, labor strikes, economic crises, sabotage or terrorist attacks and changes in ownership of the system. The objective of risk management is to reduce the effects of different domains to an acceptable level. To overcome the risk, we propose a reliable capacitated supply chain network design (RSCND model by considering random disruptions risk in both distribution centers and suppliers. The proposed study of this paper considers three objective functions and the implementation is verified using some instance.

Remembering the object you fear: brain potentials during recognition of spiders in spider-fearful individuals.

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Michalowski, Jaroslaw M; Weymar, Mathias; Hamm, Alfons O

2014-01-01

In the present study we investigated long-term memory for unpleasant, neutral and spider pictures in 15 spider-fearful and 15 non-fearful control individuals using behavioral and electrophysiological measures. During the initial (incidental) encoding, pictures were passively viewed in three separate blocks and were subsequently rated for valence and arousal. A recognition memory task was performed one week later in which old and new unpleasant, neutral and spider pictures were presented. Replicating previous results, we found enhanced memory performance and higher confidence ratings for unpleasant when compared to neutral materials in both animal fearful individuals and controls. When compared to controls high animal fearful individuals also showed a tendency towards better memory accuracy and significantly higher confidence during recognition of spider pictures, suggesting that memory of objects prompting specific fear is also facilitated in fearful individuals. In line, spider-fearful but not control participants responded with larger ERP positivity for correctly recognized old when compared to correctly rejected new spider pictures, thus showing the same effects in the neural signature of emotional memory for feared objects that were already discovered for other emotional materials. The increased fear memory for phobic materials observed in the present study in spider-fearful individuals might result in an enhanced fear response and reinforce negative beliefs aggravating anxiety symptomatology and hindering recovery.

Caffeine improves adult mice performance in the object recognition task and increases BDNF and TrkB independent on phospho-CREB immunocontent in the hippocampus.

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Costa, Marcelo S; Botton, Paulo H; Mioranzza, Sabrina; Ardais, Ana Paula; Moreira, Julia D; Souza, Diogo O; Porciúncula, Lisiane O

2008-09-01

Caffeine is one of the most psychostimulants consumed all over the world that usually presents positive effects on cognition. In this study, effects of caffeine on mice performance in the object recognition task were tested in different intertrial intervals. In addition, it was analyzed the effects of caffeine on brain derived neurotrophic factor (BDNF) and its receptor, TrkB, immunocontent to try to establish a connection between the behavioral finding and BDNF, one of the neurotrophins strictly involved in memory and learning process. CF1 mice were treated during 4 consecutive days with saline (0.9g%, i.p.) or caffeine (10mg/kg, i.p., equivalent dose corresponding to 2-3 cups of coffee). Caffeine treatment was interrupted 24h before the object recognition task analysis. In the test session performed 15min after training session, caffeine-treated mice recognized more efficiently both the familiar and the novel object. In the test session performed 90min and 24h after training session, caffeine did not change the time spent in the familiar object but increased the object recognition index, when compared to control group. Western blotting analysis of hippocampus from caffeine-treated mice revealed an increase in BDNF and TrkB immunocontent, compared to their saline-matched controls. Phospho-CREB immunocontent did not change with caffeine treatment. Our results suggest that acute treatment with caffeine improves recognition memory, and this effect may be related to an increase of the BDNF and TrkB immunocontent in the hippocampus.

Pattern recognition of neurotransmitters using multimode sensing.

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Stefan-van Staden, Raluca-Ioana; Moldoveanu, Iuliana; van Staden, Jacobus Frederick

2014-05-30

Pattern recognition is essential in chemical analysis of biological fluids. Reliable and sensitive methods for neurotransmitters analysis are needed. Therefore, we developed for pattern recognition of neurotransmitters: dopamine, epinephrine, norepinephrine a method based on multimode sensing. Multimode sensing was performed using microsensors based on diamond paste modified with 5,10,15,20-tetraphenyl-21H,23H-porphyrine, hemin and protoporphyrin IX in stochastic and differential pulse voltammetry modes. Optimized working conditions: phosphate buffer solution of pH 3.01 and KCl 0.1mol/L (as electrolyte support), were determined using cyclic voltammetry and used in all measurements. The lowest limits of quantification were: 10(-10)mol/L for dopamine and epinephrine, and 10(-11)mol/L for norepinephrine. The multimode microsensors were selective over ascorbic and uric acids and the method facilitated reliable assay of neurotransmitters in urine samples, and therefore, the pattern recognition showed high reliability (RSDneurotransmitters on biological fluids at a lower determination level than chromatographic methods. The sampling of the biological fluids referees only to the buffering (1:1, v/v) with a phosphate buffer pH 3.01, while for chromatographic methods the sampling is laborious. Accordingly with the statistic evaluation of the results at 99.00% confidence level, both modes can be used for pattern recognition and quantification of neurotransmitters with high reliability. The best multimode microsensor was the one based on diamond paste modified with protoporphyrin IX. Copyright © 2014 Elsevier B.V. All rights reserved.

The Effect of Inversion on 3- to 5-Year-Olds' Recognition of Face and Nonface Visual Objects

Science.gov (United States)

Picozzi, Marta; Cassia, Viola Macchi; Turati, Chiara; Vescovo, Elena

2009-01-01

This study compared the effect of stimulus inversion on 3- to 5-year-olds' recognition of faces and two nonface object categories matched with faces for a number of attributes: shoes (Experiment 1) and frontal images of cars (Experiments 2 and 3). The inversion effect was present for faces but not shoes at 3 years of age (Experiment 1). Analogous…

Estradiol-Induced Object Recognition Memory Consolidation Is Dependent on Activation of mTOR Signaling in the Dorsal Hippocampus

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Fortress, Ashley M.; Fan, Lu; Orr, Patrick T.; Zhao, Zaorui; Frick, Karyn M.

2013-01-01

The mammalian target of rapamycin (mTOR) signaling pathway is an important regulator of protein synthesis and is essential for various forms of hippocampal memory. Here, we asked whether the enhancement of object recognition memory consolidation produced by dorsal hippocampal infusion of 17[Beta]-estradiol (E[subscript 2]) is dependent on mTOR…

A Longitudinal Study of Cognitive Representation in Symbolic Play, Self-recognition, and Object Permanence during the Second Year.

Science.gov (United States)

Chapman, Michael

1987-01-01

Explores development of cognitive representation in 20 infants 12 to 24 months of age with regard to (l) their understanding of agency in symbolic play (agent use), (2) recognition of their own mirror image, and (3) object permanence. Results were generally consistent with developmental sequences predicted by Fischer's Skill Theory for agent use…

Improved RGB-D-T based Face Recognition

DEFF Research Database (Denmark)

Oliu Simon, Marc; Corneanu, Ciprian; Nasrollahi, Kamal

2016-01-01

years. At the same time a multimodal facial recognition is a promising approach. This paper combines the latest successes in both directions by applying deep learning Convolutional Neural Networks (CNN) to the multimodal RGB-D-T based facial recognition problem outperforming previously published results......Reliable facial recognition systems are of crucial importance in various applications from entertainment to security. Thanks to the deep-learning concepts introduced in the field, a significant improvement in the performance of the unimodal facial recognition systems has been observed in the recent...

The Reliability, Validity, and Evaluation of the Objective Structured Clinical Examination in Podiatry (Chiropody).

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Woodburn, Jim; Sutcliffe, Nick

1996-01-01

The Objective Structured Clinical Examination (OSCE), initially developed for undergraduate medical education, has been adapted for assessment of clinical skills in podiatry students. A 12-month pilot study found the test had relatively low levels of reliability, high construct and criterion validity, and good stability of performance over time.…

Shopping Behavior Recognition using a Language Modeling Analogy

NARCIS (Netherlands)

Popa, M.C.; Rothkrantz, L.J.M.; Wiggers, P.; Shan, C.

2012-01-01

Automatic understanding and recognition of human shopping behavior has many potential applications, attracting an increasing interest inthe market- ing domain. The reliability and performance of the automatic recognition system is highly in uenced by the adopted theoretical model of behavior. In

The Cambridge Car Memory Test: a task matched in format to the Cambridge Face Memory Test, with norms, reliability, sex differences, dissociations from face memory, and expertise effects.

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Dennett, Hugh W; McKone, Elinor; Tavashmi, Raka; Hall, Ashleigh; Pidcock, Madeleine; Edwards, Mark; Duchaine, Bradley

2012-06-01

Many research questions require a within-class object recognition task matched for general cognitive requirements with a face recognition task. If the object task also has high internal reliability, it can improve accuracy and power in group analyses (e.g., mean inversion effects for faces vs. objects), individual-difference studies (e.g., correlations between certain perceptual abilities and face/object recognition), and case studies in neuropsychology (e.g., whether a prosopagnosic shows a face-specific or object-general deficit). Here, we present such a task. Our Cambridge Car Memory Test (CCMT) was matched in format to the established Cambridge Face Memory Test, requiring recognition of exemplars across view and lighting change. We tested 153 young adults (93 female). Results showed high reliability (Cronbach's alpha = .84) and a range of scores suitable both for normal-range individual-difference studies and, potentially, for diagnosis of impairment. The mean for males was much higher than the mean for females. We demonstrate independence between face memory and car memory (dissociation based on sex, plus a modest correlation between the two), including where participants have high relative expertise with cars. We also show that expertise with real car makes and models of the era used in the test significantly predicts CCMT performance. Surprisingly, however, regression analyses imply that there is an effect of sex per se on the CCMT that is not attributable to a stereotypical male advantage in car expertise.

Evaluating music emotion recognition

DEFF Research Database (Denmark)

Sturm, Bob L.

2013-01-01

A fundamental problem with nearly all work in music genre recognition (MGR)is that evaluation lacks validity with respect to the principal goals of MGR. This problem also occurs in the evaluation of music emotion recognition (MER). Standard approaches to evaluation, though easy to implement, do...... not reliably differentiate between recognizing genre or emotion from music, or by virtue of confounding factors in signals (e.g., equalization). We demonstrate such problems for evaluating an MER system, and conclude with recommendations....

Guppies Show Behavioural but Not Cognitive Sex Differences in a Novel Object Recognition Test.

Directory of Open Access Journals (Sweden)

Tyrone Lucon-Xiccato

Full Text Available The novel object recognition (NOR test is a widely-used paradigm to study learning and memory in rodents. NOR performance is typically measured as the preference to interact with a novel object over a familiar object based on spontaneous exploratory behaviour. In rats and mice, females usually have greater NOR ability than males. The NOR test is now available for a large number of species, including fish, but sex differences have not been properly tested outside of rodents. We compared male and female guppies (Poecilia reticulata in a NOR test to study whether sex differences exist also for fish. We focused on sex differences in both performance and behaviour of guppies during the test. In our experiment, adult guppies expressed a preference for the novel object as most rodents and other species do. When we looked at sex differences, we found the two sexes showed a similar preference for the novel object over the familiar object, suggesting that male and female guppies have similar NOR performances. Analysis of behaviour revealed that males were more inclined to swim in the proximity of the two objects than females. Further, males explored the novel object at the beginning of the experiment while females did so afterwards. These two behavioural differences are possibly due to sex differences in exploration. Even though NOR performance is not different between male and female guppies, the behavioural sex differences we found could affect the results of the experiments and should be carefully considered when assessing fish memory with the NOR test.

Automatic anatomy recognition via multiobject oriented active shape models.

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Chen, Xinjian; Udupa, Jayaram K; Alavi, Abass; Torigian, Drew A

2010-12-01

This paper studies the feasibility of developing an automatic anatomy recognition (AAR) system in clinical radiology and demonstrates its operation on clinical 2D images. The anatomy recognition method described here consists of two main components: (a) multiobject generalization of OASM and (b) object recognition strategies. The OASM algorithm is generalized to multiple objects by including a model for each object and assigning a cost structure specific to each object in the spirit of live wire. The delineation of multiobject boundaries is done in MOASM via a three level dynamic programming algorithm, wherein the first level is at pixel level which aims to find optimal oriented boundary segments between successive landmarks, the second level is at landmark level which aims to find optimal location for the landmarks, and the third level is at the object level which aims to find optimal arrangement of object boundaries over all objects. The object recognition strategy attempts to find that pose vector (consisting of translation, rotation, and scale component) for the multiobject model that yields the smallest total boundary cost for all objects. The delineation and recognition accuracies were evaluated separately utilizing routine clinical chest CT, abdominal CT, and foot MRI data sets. The delineation accuracy was evaluated in terms of true and false positive volume fractions (TPVF and FPVF). The recognition accuracy was assessed (1) in terms of the size of the space of the pose vectors for the model assembly that yielded high delineation accuracy, (2) as a function of the number of objects and objects' distribution and size in the model, (3) in terms of the interdependence between delineation and recognition, and (4) in terms of the closeness of the optimum recognition result to the global optimum. When multiple objects are included in the model, the delineation accuracy in terms of TPVF can be improved to 97%-98% with a low FPVF of 0.1%-0.2%. Typically, a

Super-recognition in development: A case study of an adolescent with extraordinary face recognition skills.

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Bennetts, Rachel J; Mole, Joseph; Bate, Sarah

2017-09-01

Face recognition abilities vary widely. While face recognition deficits have been reported in children, it is unclear whether superior face recognition skills can be encountered during development. This paper presents O.B., a 14-year-old female with extraordinary face recognition skills: a "super-recognizer" (SR). O.B. demonstrated exceptional face-processing skills across multiple tasks, with a level of performance that is comparable to adult SRs. Her superior abilities appear to be specific to face identity: She showed an exaggerated face inversion effect and her superior abilities did not extend to object processing or non-identity aspects of face recognition. Finally, an eye-movement task demonstrated that O.B. spent more time than controls examining the nose - a pattern previously reported in adult SRs. O.B. is therefore particularly skilled at extracting and using identity-specific facial cues, indicating that face and object recognition are dissociable during development, and that super recognition can be detected in adolescence.

Evaluation of the reliability of transport networks based on the stochastic flow of moving objects

International Nuclear Information System (INIS)

Wu Weiwei; Ning, Angelika; Ning Xuanxi

2008-01-01

In transport networks, human beings are moving objects whose moving direction is stochastic in emergency situations. Based on this idea, a new model-stochastic moving network (SMN) is proposed. It is different from binary-state networks and stochastic-flow networks. The flow of SMNs has multiple-saturated states, that correspond to different flow values in each arc. In this paper, we try to evaluate the system reliability, defined as the probability that the saturated flow of the network is not less than a given demand d. Based on this new model, we obtain the flow probability distribution of every arc by simulation. An algorithm based on the blocking cutset of the SMN is proposed to evaluate the network reliability. An example is used to show how to calculate the corresponding reliabilities for different given demands of the SMN. Simulation experiments of different size were made and the system reliability precision was calculated. The precision of simulation results also discussed

Self-Recognition in Autistic Children.

Science.gov (United States)

Dawson, Geraldine; McKissick, Fawn Celeste

1984-01-01

Fifteen autistic children (four to six years old) were assessed for visual self-recognition ability, as well as for object permanence and gestural imitation. It was found that 13 of 15 autistic children showed evidence of self-recognition. Consistent relationships were suggested between self-cognition and object permanence but not between…

Genetic specificity of face recognition.

Science.gov (United States)

Shakeshaft, Nicholas G; Plomin, Robert

2015-10-13

Specific cognitive abilities in diverse domains are typically found to be highly heritable and substantially correlated with general cognitive ability (g), both phenotypically and genetically. Recent twin studies have found the ability to memorize and recognize faces to be an exception, being similarly heritable but phenotypically substantially uncorrelated both with g and with general object recognition. However, the genetic relationships between face recognition and other abilities (the extent to which they share a common genetic etiology) cannot be determined from phenotypic associations. In this, to our knowledge, first study of the genetic associations between face recognition and other domains, 2,000 18- and 19-year-old United Kingdom twins completed tests assessing their face recognition, object recognition, and general cognitive abilities. Results confirmed the substantial heritability of face recognition (61%), and multivariate genetic analyses found that most of this genetic influence is unique and not shared with other cognitive abilities.

Extended object-oriented Petri net model for mission reliability simulation of repairable PMS with common cause failures

International Nuclear Information System (INIS)

Wu, Xin-yang; Wu, Xiao-Yue

2015-01-01

Phased Mission Systems (PMS) have several phases with different success criteria. Generally, traditional analytical methods need to make some assumptions when they are applied for reliability evaluation and analysis of complex PMS, for example, the components are non-repairable or components are not subjected to common cause failures (CCF). However, the evaluation and analysis results may be inapplicable when the assumptions do not agree with practical situation. In this article, we propose an extended object-oriented Petri net (EOOPN) model for mission reliability simulation of repairable PMS with CCFs. Based on object-oriented Petri net (OOPN), EOOPN defines four reusable sub-models to depict PMS at system, phase, or component levels respectively, logic transitions to depict complex components reliability logics in a more readable form, and broadcast place to transmit shared information among components synchronously. After extension, EOOPN could deal with repairable PMS with both external and internal CCFs conveniently. The mission reliability modelling, simulation and analysis using EOOPN are illustrated by a PMS example. The results demonstrate that the proposed EOOPN model is effective. - Highlights: • EOOPN model was effective in reliability simulation for repairable PMS with CCFs. • EOOPN had modular and hierarchical structure. • New elements of EOOPN made the modelling process more convenient and friendlier. • EOOPN had better model reusability and readability than other PNs

Predictive Coding Strategies for Invariant Object Recognition and Volitional Motion Control in Neuromorphic Agents

Science.gov (United States)

2015-09-02

model for scene understanding was proposed based on deep convolutional neural networks to improve recognition accuracy. Facial expression recognition ...A deep-learning-based model for facial expression recognition was formulated. It could recognize emotional status of people regardless of...CVPRW), 2014 IEEE Conference on. IEEE, 2014. DISTRIBUTION A: Distribution approved for public release. 4 Facial Expression Recognition

Automatic anatomy recognition on CT images with pathology

Science.gov (United States)

Huang, Lidong; Udupa, Jayaram K.; Tong, Yubing; Odhner, Dewey; Torigian, Drew A.

2016-03-01

Body-wide anatomy recognition on CT images with pathology becomes crucial for quantifying body-wide disease burden. This, however, is a challenging problem because various diseases result in various abnormalities of objects such as shape and intensity patterns. We previously developed an automatic anatomy recognition (AAR) system [1] whose applicability was demonstrated on near normal diagnostic CT images in different body regions on 35 organs. The aim of this paper is to investigate strategies for adapting the previous AAR system to diagnostic CT images of patients with various pathologies as a first step toward automated body-wide disease quantification. The AAR approach consists of three main steps - model building, object recognition, and object delineation. In this paper, within the broader AAR framework, we describe a new strategy for object recognition to handle abnormal images. In the model building stage an optimal threshold interval is learned from near-normal training images for each object. This threshold is optimally tuned to the pathological manifestation of the object in the test image. Recognition is performed following a hierarchical representation of the objects. Experimental results for the abdominal body region based on 50 near-normal images used for model building and 20 abnormal images used for object recognition show that object localization accuracy within 2 voxels for liver and spleen and 3 voxels for kidney can be achieved with the new strategy.

A validated set of tool pictures with matched objects and non-objects for laterality research.

Science.gov (United States)

Verma, Ark; Brysbaert, Marc

2015-01-01

Neuropsychological and neuroimaging research has established that knowledge related to tool use and tool recognition is lateralized to the left cerebral hemisphere. Recently, behavioural studies with the visual half-field technique have confirmed the lateralization. A limitation of this research was that different sets of stimuli had to be used for the comparison of tools to other objects and objects to non-objects. Therefore, we developed a new set of stimuli containing matched triplets of tools, other objects and non-objects. With the new stimulus set, we successfully replicated the findings of no visual field advantage for objects in an object recognition task combined with a significant right visual field advantage for tools in a tool recognition task. The set of stimuli is available as supplemental data to this article.

A systematic review of reliability and objective criterion-related validity of physical activity questionnaires

Directory of Open Access Journals (Sweden)

Helmerhorst Hendrik JF

2012-08-01

Full Text Available Abstract Physical inactivity is one of the four leading risk factors for global mortality. Accurate measurement of physical activity (PA and in particular by physical activity questionnaires (PAQs remains a challenge. The aim of this paper is to provide an updated systematic review of the reliability and validity characteristics of existing and more recently developed PAQs and to quantitatively compare the performance between existing and newly developed PAQs. A literature search of electronic databases was performed for studies assessing reliability and validity data of PAQs using an objective criterion measurement of PA between January 1997 and December 2011. Articles meeting the inclusion criteria were screened and data were extracted to provide a systematic overview of measurement properties. Due to differences in reported outcomes and criterion methods a quantitative meta-analysis was not possible. In total, 31 studies testing 34 newly developed PAQs, and 65 studies examining 96 existing PAQs were included. Very few PAQs showed good results on both reliability and validity. Median reliability correlation coefficients were 0.62–0.71 for existing, and 0.74–0.76 for new PAQs. Median validity coefficients ranged from 0.30–0.39 for existing, and from 0.25–0.41 for new PAQs. Although the majority of PAQs appear to have acceptable reliability, the validity is moderate at best. Newly developed PAQs do not appear to perform substantially better than existing PAQs in terms of reliability and validity. Future PAQ studies should include measures of absolute validity and the error structure of the instrument.

A systematic review of reliability and objective criterion-related validity of physical activity questionnaires

Science.gov (United States)

2012-01-01

Physical inactivity is one of the four leading risk factors for global mortality. Accurate measurement of physical activity (PA) and in particular by physical activity questionnaires (PAQs) remains a challenge. The aim of this paper is to provide an updated systematic review of the reliability and validity characteristics of existing and more recently developed PAQs and to quantitatively compare the performance between existing and newly developed PAQs. A literature search of electronic databases was performed for studies assessing reliability and validity data of PAQs using an objective criterion measurement of PA between January 1997 and December 2011. Articles meeting the inclusion criteria were screened and data were extracted to provide a systematic overview of measurement properties. Due to differences in reported outcomes and criterion methods a quantitative meta-analysis was not possible. In total, 31 studies testing 34 newly developed PAQs, and 65 studies examining 96 existing PAQs were included. Very few PAQs showed good results on both reliability and validity. Median reliability correlation coefficients were 0.62–0.71 for existing, and 0.74–0.76 for new PAQs. Median validity coefficients ranged from 0.30–0.39 for existing, and from 0.25–0.41 for new PAQs. Although the majority of PAQs appear to have acceptable reliability, the validity is moderate at best. Newly developed PAQs do not appear to perform substantially better than existing PAQs in terms of reliability and validity. Future PAQ studies should include measures of absolute validity and the error structure of the instrument. PMID:22938557

Does long-term object priming depend on the explicit detection of object identity at encoding?

Directory of Open Access Journals (Sweden)

Carlos Alexandre Gomes

2015-03-01

Full Text Available It is currently unclear whether objects have to be explicitly identified at encoding for reliable behavioural long-term object priming to occur. We conducted two experiments that investigated long-term object and non-object priming using a selective-attention encoding manipulation that reduces explicit object identification. In Experiment 1, participants either counted dots flashed within an object picture (shallow encoding or engaged in an animacy task (deep encoding at study, whereas, at test, they performed an object-decision task. Priming, as measured by reaction times, was observed for both types of encoding, and was of equivalent magnitude. In Experiment 2, non-object priming (faster reaction times for studied relative to unstudied non-objects was also obtained under the same selective-attention encoding manipulation as in Experiment 1, and the magnitude of the priming effect was equivalent between experiments. In contrast, we observed a linear decrement in recognition memory accuracy across conditions (deep encoding of Experiment 1 > shallow encoding Experiment 1 > shallow encoding of Experiment 2, suggesting that priming was not contaminated by explicit memory strategies. We argue that our results are more consistent with the identification/production framework than the perceptual/conceptual distinction, and we conclude that priming of pictures largely ignored at encoding can be subserved by the automatic retrieval of two types of instances: one at the motor-level and another at an object-decision level.

Visual perspective in autobiographical memories: reliability, consistency, and relationship to objective memory performance.

Science.gov (United States)

Siedlecki, Karen L

2015-01-01

Visual perspective in autobiographical memories was examined in terms of reliability, consistency, and relationship to objective memory performance in a sample of 99 individuals. Autobiographical memories may be recalled from two visual perspectives--a field perspective in which individuals experience the memory through their own eyes, or an observer perspective in which individuals experience the memory from the viewpoint of an observer in which they can see themselves. Participants recalled nine word-cued memories that differed in emotional valence (positive, negative and neutral) and rated their memories on 18 scales. Results indicate that visual perspective was the most reliable memory characteristic overall and is consistently related to emotional intensity at the time of recall and amount of emotion experienced during the memory. Visual perspective is unrelated to memory for words, stories, abstract line drawings or faces.

Age, environment, object recognition and morphological diversity of GFAP-immunolabeled astrocytes.

Science.gov (United States)

Diniz, Daniel Guerreiro; de Oliveira, Marcus Augusto; de Lima, Camila Mendes; Fôro, César Augusto Raiol; Sosthenes, Marcia Consentino Kronka; Bento-Torres, João; da Costa Vasconcelos, Pedro Fernando; Anthony, Daniel Clive; Diniz, Cristovam Wanderley Picanço

2016-10-10

Few studies have explored the glial response to a standard environment and how the response may be associated with age-related cognitive decline in learning and memory. Here we investigated aging and environmental influences on hippocampal-dependent tasks and on the morphology of an unbiased selected population of astrocytes from the molecular layer of dentate gyrus, which is the main target of perforant pathway. Six and twenty-month-old female, albino Swiss mice were housed, from weaning, in a standard or enriched environment, including running wheels for exercise and tested for object recognition and contextual memories. Young adult and aged subjects, independent of environment, were able to distinguish familiar from novel objects. All experimental groups, except aged mice from standard environment, distinguish stationary from displaced objects. Young adult but not aged mice, independent of environment, were able to distinguish older from recent objects. Only young mice from an enriched environment were able to distinguish novel from familiar contexts. Unbiased selected astrocytes from the molecular layer of the dentate gyrus were reconstructed in three-dimensions and classified using hierarchical cluster analysis of bimodal or multimodal morphological features. We found two morphological phenotypes of astrocytes and we designated type I the astrocytes that exhibited significantly higher values of morphological complexity as compared with type II. Complexity = [Sum of the terminal orders + Number of terminals] × [Total branch length/Number of primary branches]. On average, type I morphological complexity seems to be much more sensitive to age and environmental influences than that of type II. Indeed, aging and environmental impoverishment interact and reduce the morphological complexity of type I astrocytes at a point that they could not be distinguished anymore from type II. We suggest these two types of astrocytes may have different physiological roles

Adults' strategies for simple addition and multiplication: verbal self-reports and the operand recognition paradigm.

Science.gov (United States)

Metcalfe, Arron W S; Campbell, Jamie I D

2011-05-01

Accurate measurement of cognitive strategies is important in diverse areas of psychological research. Strategy self-reports are a common measure, but C. Thevenot, M. Fanget, and M. Fayol (2007) proposed a more objective method to distinguish different strategies in the context of mental arithmetic. In their operand recognition paradigm, speed of recognition memory for problem operands after solving a problem indexes strategy (e.g., direct memory retrieval vs. a procedural strategy). Here, in 2 experiments, operand recognition time was the same following simple addition or multiplication, but, consistent with a wide variety of previous research, strategy reports indicated much greater use of procedures (e.g., counting) for addition than multiplication. Operation, problem size (e.g., 2 + 3 vs. 8 + 9), and operand format (digits vs. words) had interactive effects on reported procedure use that were not reflected in recognition performance. Regression analyses suggested that recognition time was influenced at least as much by the relative difficulty of the preceding problem as by the strategy used. The findings indicate that the operand recognition paradigm is not a reliable substitute for strategy reports and highlight the potential impact of difficulty-related carryover effects in sequential cognitive tasks.

Practical solutions for multi-objective optimization: An application to system reliability design problems

International Nuclear Information System (INIS)

Taboada, Heidi A.; Baheranwala, Fatema; Coit, David W.; Wattanapongsakorn, Naruemon

2007-01-01

For multiple-objective optimization problems, a common solution methodology is to determine a Pareto optimal set. Unfortunately, these sets are often large and can become difficult to comprehend and consider. Two methods are presented as practical approaches to reduce the size of the Pareto optimal set for multiple-objective system reliability design problems. The first method is a pseudo-ranking scheme that helps the decision maker select solutions that reflect his/her objective function priorities. In the second approach, we used data mining clustering techniques to group the data by using the k-means algorithm to find clusters of similar solutions. This provides the decision maker with just k general solutions to choose from. With this second method, from the clustered Pareto optimal set, we attempted to find solutions which are likely to be more relevant to the decision maker. These are solutions where a small improvement in one objective would lead to a large deterioration in at least one other objective. To demonstrate how these methods work, the well-known redundancy allocation problem was solved as a multiple objective problem by using the NSGA genetic algorithm to initially find the Pareto optimal solutions, and then, the two proposed methods are applied to prune the Pareto set

Using standardized video cases for assessment of medical communication skills: reliability of an objective structured video examination by computer

NARCIS (Netherlands)

Hulsman, R. L.; Mollema, E. D.; Oort, F. J.; Hoos, A. M.; de Haes, J. C. J. M.

2006-01-01

OBJECTIVE: Using standardized video cases in a computerized objective structured video examination (OSVE) aims to measure cognitive scripts underlying overt communication behavior by questions on knowledge, understanding and performance. In this study the reliability of the OSVE assessment is

Object Recognition in Flight: How Do Bees Distinguish between 3D Shapes?

Science.gov (United States)

Werner, Annette; Stürzl, Wolfgang; Zanker, Johannes

2016-01-01

Honeybees (Apis mellifera) discriminate multiple object features such as colour, pattern and 2D shape, but it remains unknown whether and how bees recover three-dimensional shape. Here we show that bees can recognize objects by their three-dimensional form, whereby they employ an active strategy to uncover the depth profiles. We trained individual, free flying honeybees to collect sugar water from small three-dimensional objects made of styrofoam (sphere, cylinder, cuboids) or folded paper (convex, concave, planar) and found that bees can easily discriminate between these stimuli. We also tested possible strategies employed by the bees to uncover the depth profiles. For the card stimuli, we excluded overall shape and pictorial features (shading, texture gradients) as cues for discrimination. Lacking sufficient stereo vision, bees are known to use speed gradients in optic flow to detect edges; could the bees apply this strategy also to recover the fine details of a surface depth profile? Analysing the bees' flight tracks in front of the stimuli revealed specific combinations of flight maneuvers (lateral translations in combination with yaw rotations), which are particularly suitable to extract depth cues from motion parallax. We modelled the generated optic flow and found characteristic patterns of angular displacement corresponding to the depth profiles of our stimuli: optic flow patterns from pure translations successfully recovered depth relations from the magnitude of angular displacements, additional rotation provided robust depth information based on the direction of the displacements; thus, the bees flight maneuvers may reflect an optimized visuo-motor strategy to extract depth structure from motion signals. The robustness and simplicity of this strategy offers an efficient solution for 3D-object-recognition without stereo vision, and could be employed by other flying insects, or mobile robots.

When is the hippocampus involved in recognition memory?

OpenAIRE

Barker, Gareth R. I.; Warburton, Elizabeth C.

2011-01-01

The role of the hippocampus in recognition memory is controversial. Recognition memory judgments may be made using different types of information, including object familiarity, an object's spatial location, or when an object was encountered. Experiment 1 examined the role of the hippocampus in recognition memory tasks that required the animals to use these different types of mnemonic information. Rats with bilateral cytotoxic lesions in the hippocampus or perirhinal or prefrontal cortex were ...

Application of objective clinical human reliability analysis (OCHRA) in assessment of technical performance in laparoscopic rectal cancer surgery.

Science.gov (United States)

Foster, J D; Miskovic, D; Allison, A S; Conti, J A; Ockrim, J; Cooper, E J; Hanna, G B; Francis, N K

2016-06-01

Laparoscopic rectal resection is technically challenging, with outcomes dependent upon technical performance. No robust objective assessment tool exists for laparoscopic rectal resection surgery. This study aimed to investigate the application of the objective clinical human reliability analysis (OCHRA) technique for assessing technical performance of laparoscopic rectal surgery and explore the validity and reliability of this technique. Laparoscopic rectal cancer resection operations were described in the format of a hierarchical task analysis. Potential technical errors were defined. The OCHRA technique was used to identify technical errors enacted in videos of twenty consecutive laparoscopic rectal cancer resection operations from a single site. The procedural task, spatial location, and circumstances of all identified errors were logged. Clinical validity was assessed through correlation with clinical outcomes; reliability was assessed by test-retest. A total of 335 execution errors identified, with a median 15 per operation. More errors were observed during pelvic tasks compared with abdominal tasks (p technical performance of laparoscopic rectal surgery.

Episodic Short-Term Recognition Requires Encoding into Visual Working Memory: Evidence from Probe Recognition after Letter Report.

Science.gov (United States)

Poth, Christian H; Schneider, Werner X

2016-01-01

Human vision is organized in discrete processing episodes (e.g., eye fixations or task-steps). Object information must be transmitted across episodes to enable episodic short-term recognition: recognizing whether a current object has been seen in a previous episode. We ask whether episodic short-term recognition presupposes that objects have been encoded into capacity-limited visual working memory (VWM), which retains visual information for report. Alternatively, it could rely on the activation of visual features or categories that occurs before encoding into VWM. We assessed the dependence of episodic short-term recognition on VWM by a new paradigm combining letter report and probe recognition. Participants viewed displays of 10 letters and reported as many as possible after a retention interval (whole report). Next, participants viewed a probe letter and indicated whether it had been one of the 10 letters (probe recognition). In Experiment 1, probe recognition was more accurate for letters that had been encoded into VWM (reported letters) compared with non-encoded letters (non-reported letters). Interestingly, those letters that participants reported in their whole report had been near to one another within the letter displays. This suggests that the encoding into VWM proceeded in a spatially clustered manner. In Experiment 2, participants reported only one of 10 letters (partial report) and probes either referred to this letter, to letters that had been near to it, or far from it. Probe recognition was more accurate for near than for far letters, although none of these letters had to be reported. These findings indicate that episodic short-term recognition is constrained to a small number of simultaneously presented objects that have been encoded into VWM.

Episodic Short-Term Recognition Requires Encoding into Visual Working Memory: Evidence from Probe Recognition after Letter Report

Directory of Open Access Journals (Sweden)

Christian H. Poth

2016-09-01

Full Text Available Human vision is organized in discrete processing episodes (e.g. eye fixations or task-steps. Object information must be transmitted across episodes to enable episodic short-term recognition: recognizing whether a current object has been seen in a previous episode. We ask whether episodic short-term recognition presupposes that objects have been encoded into capacity-limited visual working memory (VWM, which retains visual information for report. Alternatively, it could rely on the activation of visual features or categories that occurs before encoding into VWM. We assessed the dependence of episodic short-term recognition on VWM by a new paradigm combining letter report and probe recognition. Participants viewed displays of ten letters and reported as many as possible after a retention interval (whole report. Next, participants viewed a probe letter and indicated whether it had been one of the ten letters (probe recognition. In Experiment 1, probe recognition was more accurate for letters that had been encoded into VWM (reported letters compared with non-encoded letters (non-reported letters. Interestingly, those letters that participants reported in their whole report had been near to one another within the letter displays. This suggests that the encoding into VWM proceeded in a spatially clustered manner. In Experiment 2 participants reported only one of ten letters (partial report and probes either referred to this letter, to letters that had been near to it, or far from it. Probe recognition was more accurate for near than for far letters, although none of these letters had to be reported. These findings indicate that episodic short-term recognition is constrained to a small number of simultaneously presented objects that have been encoded into VWM.

Acute fasting inhibits central caspase-1 activity reducing anxiety-like behavior and increasing novel object and object location recognition.

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Towers, Albert E; Oelschlager, Maci L; Patel, Jay; Gainey, Stephen J; McCusker, Robert H; Freund, Gregory G

2017-06-01

Inflammation within the central nervous system (CNS) is frequently comorbid with anxiety. Importantly, the pro-inflammatory cytokine most commonly associated with anxiety is IL-1β. The bioavailability and activity of IL-1β are regulated by caspase-1-dependent proteolysis vis-a-vis the inflammasome. Thus, interventions regulating the activation or activity of caspase-1 should reduce anxiety especially in states that foster IL-1β maturation. Male C57BL/6j, C57BL/6j mice treated with the capase-1 inhibitor biotin-YVAD-cmk, caspase-1 knockout (KO) mice and IL-1R1 KO mice were fasted for 24h or allowed ad libitum access to food. Immediately after fasting, caspase-1 activity was measured in brain region homogenates while activated caspase-1 was localized in the brain by immunohistochemistry. Mouse anxiety-like behavior and cognition were tested using the elevated zero maze and novel object/object location tasks, respectively. A 24h fast in mice reduced the activity of caspase-1 in whole brain and in the prefrontal cortex, amygdala, hippocampus, and hypothalamus by 35%, 25%, 40%, 40%, and 40% respectively. A 24h fast also reduced anxiety-like behavior by 40% and increased novel object and object location recognition by 21% and 31%, respectively. IL-1β protein, however, was not reduced in the brain by fasting. ICV administration of YVAD decreased caspase-1 activity in the prefrontal cortex and amygdala by 55%, respectively leading to a 64% reduction in anxiety like behavior. Importantly, when caspase-1 KO or IL1-R1 KO mice are fasted, no fasting-dependent reduction in anxiety-like behavior was observed. Results indicate that fasting decrease anxiety-like behavior and improves memory by a mechanism tied to reducing caspase-1 activity throughout the brain. Copyright © 2017 Elsevier Inc. All rights reserved.

Poka Yoke system based on image analysis and object recognition

Science.gov (United States)

Belu, N.; Ionescu, L. M.; Misztal, A.; Mazăre, A.

2015-11-01

Poka Yoke is a method of quality management which is related to prevent faults from arising during production processes. It deals with “fail-sating” or “mistake-proofing”. The Poka-yoke concept was generated and developed by Shigeo Shingo for the Toyota Production System. Poka Yoke is used in many fields, especially in monitoring production processes. In many cases, identifying faults in a production process involves a higher cost than necessary cost of disposal. Usually, poke yoke solutions are based on multiple sensors that identify some nonconformities. This means the presence of different equipment (mechanical, electronic) on production line. As a consequence, coupled with the fact that the method itself is an invasive, affecting the production process, would increase its price diagnostics. The bulky machines are the means by which a Poka Yoke system can be implemented become more sophisticated. In this paper we propose a solution for the Poka Yoke system based on image analysis and identification of faults. The solution consists of a module for image acquisition, mid-level processing and an object recognition module using associative memory (Hopfield network type). All are integrated into an embedded system with AD (Analog to Digital) converter and Zync 7000 (22 nm technology).

Probability-Based Recognition Framework for Underwater Landmarks Using Sonar Images †.

Science.gov (United States)

Lee, Yeongjun; Choi, Jinwoo; Ko, Nak Yong; Choi, Hyun-Taek

2017-08-24

This paper proposes a probability-based framework for recognizing underwater landmarks using sonar images. Current recognition methods use a single image, which does not provide reliable results because of weaknesses of the sonar image such as unstable acoustic source, many speckle noises, low resolution images, single channel image, and so on. However, using consecutive sonar images, if the status-i.e., the existence and identity (or name)-of an object is continuously evaluated by a stochastic method, the result of the recognition method is available for calculating the uncertainty, and it is more suitable for various applications. Our proposed framework consists of three steps: (1) candidate selection, (2) continuity evaluation, and (3) Bayesian feature estimation. Two probability methods-particle filtering and Bayesian feature estimation-are used to repeatedly estimate the continuity and feature of objects in consecutive images. Thus, the status of the object is repeatedly predicted and updated by a stochastic method. Furthermore, we develop an artificial landmark to increase detectability by an imaging sonar, which we apply to the characteristics of acoustic waves, such as instability and reflection depending on the roughness of the reflector surface. The proposed method is verified by conducting basin experiments, and the results are presented.

Implementation of PATREC nuclear reliability program in LISP

International Nuclear Information System (INIS)

Patterson-Hine, F.A.; Koen, B.V.

1985-01-01

The reliability of large systems can be represented by reliability fault trees that contain the failure probabilities for the individual elements in the original network and the logical connectives that describe the interdependence of those probabilities. The PATREC 1 computer code was written to demonstrate the feasibility of using list processing techniques for the resolution of a reliability fault tree by pattern recognition. PATREC 1 was written in PL/1 and is used widely in France. The fault tree is expressed as a linked data structure, oriented, mapped into an end-ordered traverse, and used to retrieve known patterns stored as a linked-tree library. The basic idea of pattern recognition is to prune the fault tree by identifying known patterns, retrieving the corresponding mathematical equation, and evaluating the replacement leaves. This process is repeated until the original tree is reduced to a single leaf - the system reliability

Bidirectional Modulation of Recognition Memory.

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Ho, Jonathan W; Poeta, Devon L; Jacobson, Tara K; Zolnik, Timothy A; Neske, Garrett T; Connors, Barry W; Burwell, Rebecca D

2015-09-30

Perirhinal cortex (PER) has a well established role in the familiarity-based recognition of individual items and objects. For example, animals and humans with perirhinal damage are unable to distinguish familiar from novel objects in recognition memory tasks. In the normal brain, perirhinal neurons respond to novelty and familiarity by increasing or decreasing firing rates. Recent work also implicates oscillatory activity in the low-beta and low-gamma frequency bands in sensory detection, perception, and recognition. Using optogenetic methods in a spontaneous object exploration (SOR) task, we altered recognition memory performance in rats. In the SOR task, normal rats preferentially explore novel images over familiar ones. We modulated exploratory behavior in this task by optically stimulating channelrhodopsin-expressing perirhinal neurons at various frequencies while rats looked at novel or familiar 2D images. Stimulation at 30-40 Hz during looking caused rats to treat a familiar image as if it were novel by increasing time looking at the image. Stimulation at 30-40 Hz was not effective in increasing exploration of novel images. Stimulation at 10-15 Hz caused animals to treat a novel image as familiar by decreasing time looking at the image, but did not affect looking times for images that were already familiar. We conclude that optical stimulation of PER at different frequencies can alter visual recognition memory bidirectionally. Significance statement: Recognition of novelty and familiarity are important for learning, memory, and decision making. Perirhinal cortex (PER) has a well established role in the familiarity-based recognition of individual items and objects, but how novelty and familiarity are encoded and transmitted in the brain is not known. Perirhinal neurons respond to novelty and familiarity by changing firing rates, but recent work suggests that brain oscillations may also be important for recognition. In this study, we showed that stimulation of

An Unsupervised Approach to Activity Recognition and Segmentation based on Object-Use Fingerprints

DEFF Research Database (Denmark)

Gu, Tao; Chen, Shaxun; Tao, Xianping

2010-01-01

Human activity recognition is an important task which has many potential applications. In recent years, researchers from pervasive computing are interested in deploying on-body sensors to collect observations and applying machine learning techniques to model and recognize activities. Supervised...... machine learning techniques typically require an appropriate training process in which training data need to be labeled manually. In this paper, we propose an unsupervised approach based on object-use fingerprints to recognize activities without human labeling. We show how to build our activity models...... a trace and detect the boundary of any two adjacent activities. We develop a wearable RFID system and conduct a real-world trace collection done by seven volunteers in a smart home over a period of 2 weeks. We conduct comprehensive experimental evaluations and comparison study. The results show that our...

Investigations into the involvement of NMDA mechanisms in recognition memory.

Science.gov (United States)

Warburton, E Clea; Barker, Gareth R I; Brown, Malcom W

2013-11-01

This review will focus on evidence showing that NMDA receptor neurotransmission is critical for synaptic plasticity processes within brain regions known to be necessary for the formation of object recognition memories. The aim will be to provide evidence concerning NMDA mechanisms related to recognition memory processes and show that recognition memory for objects, places or associations between objects and places depends on NMDA neurotransmission within the perirhinal cortex, temporal association cortex medial prefrontal cortex and hippocampus. Administration of the NMDA antagonist AP5, selectively into each of these brain regions has revealed that the extent of the involvement NMDA receptors appears dependent on the type of information required to solve the recognition memory task; thus NMDA receptors in the perirhinal cortex are crucial for the encoding of long-term recognition memory for objects, and object-in-place associations, but not for short-term recognition memory or for retrieval. In contrast the hippocampus and medial prefrontal cortex are required for both long-term and short-term recognition memory for places or associations between objects and places, or for recognition memory tasks that have a temporal component. Such studies have therefore confirmed that the multiple brain regions make distinct contributions to recognition memory but in addition that more than one synaptic plasticity process must be involved. This article is part of the Special Issue entitled 'Glutamate Receptor-Dependent Synaptic Plasticity'. Copyright © 2013 The Authors. Published by Elsevier Ltd.. All rights reserved.

Improved object optimal synthetic description, modeling, learning, and discrimination by GEOGINE computational kernel

Science.gov (United States)

Fiorini, Rodolfo A.; Dacquino, Gianfranco

2005-03-01

GEOGINE (GEOmetrical enGINE), a state-of-the-art OMG (Ontological Model Generator) based on n-D Tensor Invariants for n-Dimensional shape/texture optimal synthetic representation, description and learning, was presented in previous conferences elsewhere recently. Improved computational algorithms based on the computational invariant theory of finite groups in Euclidean space and a demo application is presented. Progressive model automatic generation is discussed. GEOGINE can be used as an efficient computational kernel for fast reliable application development and delivery in advanced biomedical engineering, biometric, intelligent computing, target recognition, content image retrieval, data mining technological areas mainly. Ontology can be regarded as a logical theory accounting for the intended meaning of a formal dictionary, i.e., its ontological commitment to a particular conceptualization of the world object. According to this approach, "n-D Tensor Calculus" can be considered a "Formal Language" to reliably compute optimized "n-Dimensional Tensor Invariants" as specific object "invariant parameter and attribute words" for automated n-Dimensional shape/texture optimal synthetic object description by incremental model generation. The class of those "invariant parameter and attribute words" can be thought as a specific "Formal Vocabulary" learned from a "Generalized Formal Dictionary" of the "Computational Tensor Invariants" language. Even object chromatic attributes can be effectively and reliably computed from object geometric parameters into robust colour shape invariant characteristics. As a matter of fact, any highly sophisticated application needing effective, robust object geometric/colour invariant attribute capture and parameterization features, for reliable automated object learning and discrimination can deeply benefit from GEOGINE progressive automated model generation computational kernel performance. Main operational advantages over previous

Development of a Pattern Recognition Methodology for Determining Operationally Optimal Heat Balance Instrumentation Calibration Schedules

Energy Technology Data Exchange (ETDEWEB)

Kurt Beran; John Christenson; Dragos Nica; Kenny Gross

2002-12-15

The goal of the project is to enable plant operators to detect with high sensitivity and reliability the onset of decalibration drifts in all of the instrumentation used as input to the reactor heat balance calculations. To achieve this objective, the collaborators developed and implemented at DBNPS an extension of the Multivariate State Estimation Technique (MSET) pattern recognition methodology pioneered by ANAL. The extension was implemented during the second phase of the project and fully achieved the project goal.

Short exposure to a diet rich in both fat and sugar or sugar alone impairs place, but not object recognition memory in rats.

Science.gov (United States)

Beilharz, Jessica E; Maniam, Jayanthi; Morris, Margaret J

2014-03-01

High energy diets have been shown to impair cognition however, the rapidity of these effects, and the dietary component/s responsible are currently unclear. We conducted two experiments in rats to examine the effects of short-term exposure to a diet rich in sugar and fat or rich in sugar on object (perirhinal-dependent) and place (hippocampal-dependent) recognition memory, and the role of inflammatory mediators in these responses. In Experiment 1, rats fed a cafeteria style diet containing chow supplemented with lard, cakes, biscuits, and a 10% sucrose solution performed worse on the place, but not the object recognition task, than chow fed control rats when tested after 5, 11, and 20 days. In Experiment 2, rats fed the cafeteria style diet either with or without sucrose and rats fed chow supplemented with sucrose also performed worse on the place, but not the object recognition task when tested after 5, 11, and 20 days. Rats fed the cafeteria diets consumed five times more energy than control rats and exhibited increased plasma leptin, insulin and triglyceride concentrations; these were not affected in the sucrose only rats. Rats exposed to sucrose exhibited both increased hippocampal inflammation (TNF-α and IL-1β mRNA) and oxidative stress, as indicated by an upregulation of NRF1 mRNA compared to control rats. In contrast, these markers were not significantly elevated in rats that received the cafeteria diet without added sucrose. Hippocampal BDNF and neuritin mRNA were similar across all groups. These results show that relatively short exposures to diets rich in both fat and sugar or rich in sugar, impair hippocampal-dependent place recognition memory prior to the emergence of weight differences, and suggest a role for oxidative stress and neuroinflammation in this impairment. Crown Copyright © 2013. Published by Elsevier Inc. All rights reserved.

From brain synapses to systems for learning and memory: Object recognition, spatial navigation, timed conditioning, and movement control.

Science.gov (United States)

Grossberg, Stephen

2015-09-24

This article provides an overview of neural models of synaptic learning and memory whose expression in adaptive behavior depends critically on the circuits and systems in which the synapses are embedded. It reviews Adaptive Resonance Theory, or ART, models that use excitatory matching and match-based learning to achieve fast category learning and whose learned memories are dynamically stabilized by top-down expectations, attentional focusing, and memory search. ART clarifies mechanistic relationships between consciousness, learning, expectation, attention, resonance, and synchrony. ART models are embedded in ARTSCAN architectures that unify processes of invariant object category learning, recognition, spatial and object attention, predictive remapping, and eye movement search, and that clarify how conscious object vision and recognition may fail during perceptual crowding and parietal neglect. The generality of learned categories depends upon a vigilance process that is regulated by acetylcholine via the nucleus basalis. Vigilance can get stuck at too high or too low values, thereby causing learning problems in autism and medial temporal amnesia. Similar synaptic learning laws support qualitatively different behaviors: Invariant object category learning in the inferotemporal cortex; learning of grid cells and place cells in the entorhinal and hippocampal cortices during spatial navigation; and learning of time cells in the entorhinal-hippocampal system during adaptively timed conditioning, including trace conditioning. Spatial and temporal processes through the medial and lateral entorhinal-hippocampal system seem to be carried out with homologous circuit designs. Variations of a shared laminar neocortical circuit design have modeled 3D vision, speech perception, and cognitive working memory and learning. A complementary kind of inhibitory matching and mismatch learning controls movement. This article is part of a Special Issue entitled SI: Brain and Memory

Conformal prediction for reliable machine learning theory, adaptations and applications

CERN Document Server

Balasubramanian, Vineeth; Vovk, Vladimir

2014-01-01

The conformal predictions framework is a recent development in machine learning that can associate a reliable measure of confidence with a prediction in any real-world pattern recognition application, including risk-sensitive applications such as medical diagnosis, face recognition, and financial risk prediction. Conformal Predictions for Reliable Machine Learning: Theory, Adaptations and Applications captures the basic theory of the framework, demonstrates how to apply it to real-world problems, and presents several adaptations, including active learning, change detection, and anomaly detecti

Contemporary deep recurrent learning for recognition

Science.gov (United States)

Iftekharuddin, K. M.; Alam, M.; Vidyaratne, L.

2017-05-01

Large-scale feed-forward neural networks have seen intense application in many computer vision problems. However, these networks can get hefty and computationally intensive with increasing complexity of the task. Our work, for the first time in literature, introduces a Cellular Simultaneous Recurrent Network (CSRN) based hierarchical neural network for object detection. CSRN has shown to be more effective to solving complex tasks such as maze traversal and image processing when compared to generic feed forward networks. While deep neural networks (DNN) have exhibited excellent performance in object detection and recognition, such hierarchical structure has largely been absent in neural networks with recurrency. Further, our work introduces deep hierarchy in SRN for object recognition. The simultaneous recurrency results in an unfolding effect of the SRN through time, potentially enabling the design of an arbitrarily deep network. This paper shows experiments using face, facial expression and character recognition tasks using novel deep recurrent model and compares recognition performance with that of generic deep feed forward model. Finally, we demonstrate the flexibility of incorporating our proposed deep SRN based recognition framework in a humanoid robotic platform called NAO.

6DoF object pose measurement by a monocular manifold-based pattern recognition technique

International Nuclear Information System (INIS)

Kouskouridas, Rigas; Charalampous, Konstantinos; Gasteratos, Antonios

2012-01-01

In this paper, a novel solution to the compound problem of object recognition and 3D pose estimation is presented. An accurate measurement of the geometrical configuration of a recognized target, relative to a known coordinate system, is of fundamental importance and constitutes a prerequisite for several applications such as robot grasping or obstacle avoidance. The proposed method lays its foundations on the following assumptions: (a) the same object captured under varying viewpoints and perspectives represents data that could be projected onto a well-established and highly distinguishable subspace; (b) totally different objects observed under the same viewpoints and perspectives share identical 3D pose that can be sufficiently modeled to produce a generalized model. Toward this end, we propose an advanced architecture that allows both recognizing patterns and providing efficient solution for 6DoF pose estimation. We employ a manifold modeling architecture that is grounded on a part-based representation of an object, which in turn, is accomplished via an unsupervised clustering of the extracted visual cues. The main contributions of the proposed framework are: (a) the proposed part-based architecture requires minimum supervision, compared to other contemporary solutions, whilst extracting new features encapsulating both appearance and geometrical attributes of the objects; (b) contrary to related projects that extract high-dimensional data, thus, increasing the complexity of the system, the proposed manifold modeling approach makes use of low dimensionality input vectors; (c) the formulation of a novel input–output space mapping that outperforms the existing dimensionality reduction schemes. Experimental results justify our theoretical claims and demonstrate the superiority of our method comparing to other related contemporary projects. (paper)

The protective effect of hesperetin and nano-hesperetin on object recognition memory in animal model of Alzheimer

Directory of Open Access Journals (Sweden)

2017-11-01

Full Text Available Background and objectives: Hesperetin (Hst, aglycone form of hesperidin, is reported to have antioxidant, anti-inflammatory and neuroprotective activities. On the other hand, the latest nanoparticle technology can help to improve the bioavailability of Hst, which is affected by the final particle size and stability. Alzheimer’s disease is a neurodegenerative disease, characterized by loss of the cognitive abilities, including memory, speech, emotions, and personality. Oxidative stress, a condition that occurs due to the imbalance in oxidant and antioxidant status, has been known to play a vital role in the pathophysiology of neurodegenerative diseases. This study was carried out in order to evaluate the protective effects of hesperetin and nano-hesperetin on memory disorder in the brains of Alzheimer’s animal models. Methods: Forty nine male rats were divided into 7 groups: control, vehicle, STZ group (rats were injected with STZ, treatment groups receiving 10 and 20 mg/kg/day of hesperetin and nano-hesperetin. Then 3 μgr/rat of (STZ was injected to the cerebroventricular of rats of all groups except the control and vehicle groups. The 4 treatment groups were gavaged by, respectively 10, 20 mg/Kg of hesperetin and nano-hesperetin for 30 days. After three weeks, recognition memory was examined by novel object recognition test. Results: The results showed that injection of STZ increased memory disorders (p≤0.001 and treatment of hesperetin and nano-hesperetin effectively decreased memory disorders (p

Recognition-induced forgetting of faces in visual long-term memory.

Science.gov (United States)

Rugo, Kelsi F; Tamler, Kendall N; Woodman, Geoffrey F; Maxcey, Ashleigh M

2017-10-01

Despite more than a century of evidence that long-term memory for pictures and words are different, much of what we know about memory comes from studies using words. Recent research examining visual long-term memory has demonstrated that recognizing an object induces the forgetting of objects from the same category. This recognition-induced forgetting has been shown with a variety of everyday objects. However, unlike everyday objects, faces are objects of expertise. As a result, faces may be immune to recognition-induced forgetting. However, despite excellent memory for such stimuli, we found that faces were susceptible to recognition-induced forgetting. Our findings have implications for how models of human memory account for recognition-induced forgetting as well as represent objects of expertise and consequences for eyewitness testimony and the justice system.

Automatic Recognition of Object Names in Literature

Science.gov (United States)

Bonnin, C.; Lesteven, S.; Derriere, S.; Oberto, A.

2008-08-01

SIMBAD is a database of astronomical objects that provides (among other things) their bibliographic references in a large number of journals. Currently, these references have to be entered manually by librarians who read each paper. To cope with the increasing number of papers, CDS develops a tool to assist the librarians in their work, taking advantage of the Dictionary of Nomenclature of Celestial Objects, which keeps track of object acronyms and of their origin. The program searches for object names directly in PDF documents by comparing the words with all the formats stored in the Dictionary of Nomenclature. It also searches for variable star names based on constellation names and for a large list of usual names such as Aldebaran or the Crab. Object names found in the documents often correspond to several astronomical objects. The system retrieves all possible matches, displays them with their object type given by SIMBAD, and lets the librarian make the final choice. The bibliographic reference can then be automatically added to the object identifiers in the database. Besides, the systematic usage of the Dictionary of Nomenclature, which is updated manually, permitted to automatically check it and to detect errors and inconsistencies. Last but not least, the program collects some additional information such as the position of the object names in the document (in the title, subtitle, abstract, table, figure caption...) and their number of occurrences. In the future, this will permit to calculate the 'weight' of an object in a reference and to provide SIMBAD users with an important new information, which will help them to find the most relevant papers in the object reference list.

Objective Prediction of Hearing Aid Benefit Across Listener Groups Using Machine Learning: Speech Recognition Performance With Binaural Noise-Reduction Algorithms.

Science.gov (United States)

Schädler, Marc R; Warzybok, Anna; Kollmeier, Birger

2018-01-01

The simulation framework for auditory discrimination experiments (FADE) was adopted and validated to predict the individual speech-in-noise recognition performance of listeners with normal and impaired hearing with and without a given hearing-aid algorithm. FADE uses a simple automatic speech recognizer (ASR) to estimate the lowest achievable speech reception thresholds (SRTs) from simulated speech recognition experiments in an objective way, independent from any empirical reference data. Empirical data from the literature were used to evaluate the model in terms of predicted SRTs and benefits in SRT with the German matrix sentence recognition test when using eight single- and multichannel binaural noise-reduction algorithms. To allow individual predictions of SRTs in binaural conditions, the model was extended with a simple better ear approach and individualized by taking audiograms into account. In a realistic binaural cafeteria condition, FADE explained about 90% of the variance of the empirical SRTs for a group of normal-hearing listeners and predicted the corresponding benefits with a root-mean-square prediction error of 0.6 dB. This highlights the potential of the approach for the objective assessment of benefits in SRT without prior knowledge about the empirical data. The predictions for the group of listeners with impaired hearing explained 75% of the empirical variance, while the individual predictions explained less than 25%. Possibly, additional individual factors should be considered for more accurate predictions with impaired hearing. A competing talker condition clearly showed one limitation of current ASR technology, as the empirical performance with SRTs lower than -20 dB could not be predicted.

Caffeine prevents disruption of memory consolidation in the inhibitory avoidance and novel object recognition tasks by scopolamine in adult mice.

Science.gov (United States)

Botton, Paulo Henrique; Costa, Marcelo S; Ardais, Ana Paula; Mioranzza, Sabrina; Souza, Diogo O; da Rocha, João Batista Teixeira; Porciúncula, Lisiane O

2010-12-25

Caffeine is a psychostimulant with positive effects on cognition. Recent studies have suggested the participation of the cholinergic system in the effects of caffeine on wakefulness. However, there are few studies assessing the contribution of cholinergic system in the cognitive enhancer properties of caffeine. In the present study, the effects of a dose and schedule of administration of caffeine that improved memory recognition were investigated on scopolamine-induced impairment of memory in adult mice. Inhibitory avoidance and novel object recognition tasks were used to assess learning and memory. Caffeine (10mg/kg, i.p.) was administered during 4 consecutive days, and the treatment was interrupted 24h before scopolamine administration (2mg/kg, i.p.). Scopolamine was administered prior to or immediately after training. Short-term and long-term memory was evaluated in both tasks. In the novel object recognition task, pre treatment with caffeine prevented the disruption of short- and long-term memory by scopolamine. In the inhibitory avoidance task, caffeine prevented short- but not long-term memory disruption by pre training administration of scopolamine. Caffeine prevented short- and long-term memory disruption by post training administration of scopolamine. Both treatments did not affect locomotor activity of the animals. These findings suggest that acute treatment with caffeine followed by its withdrawal may be effective against cholinergic-induced disruption of memory assessed in an aversive and non-aversive task. Finally, our results revealed that the cholinergic system is involved in the positive effects of caffeine on cognitive functions. Copyright (c) 2010 Elsevier B.V. All rights reserved.

Image-based automatic recognition of larvae

Science.gov (United States)

Sang, Ru; Yu, Guiying; Fan, Weijun; Guo, Tiantai

2010-08-01

As the main objects, imagoes have been researched in quarantine pest recognition in these days. However, pests in their larval stage are latent, and the larvae spread abroad much easily with the circulation of agricultural and forest products. It is presented in this paper that, as the new research objects, larvae are recognized by means of machine vision, image processing and pattern recognition. More visional information is reserved and the recognition rate is improved as color image segmentation is applied to images of larvae. Along with the characteristics of affine invariance, perspective invariance and brightness invariance, scale invariant feature transform (SIFT) is adopted for the feature extraction. The neural network algorithm is utilized for pattern recognition, and the automatic identification of larvae images is successfully achieved with satisfactory results.

STDP-based spiking deep convolutional neural networks for object recognition.

Science.gov (United States)

Kheradpisheh, Saeed Reza; Ganjtabesh, Mohammad; Thorpe, Simon J; Masquelier, Timothée

2018-03-01

Previous studies have shown that spike-timing-dependent plasticity (STDP) can be used in spiking neural networks (SNN) to extract visual features of low or intermediate complexity in an unsupervised manner. These studies, however, used relatively shallow architectures, and only one layer was trainable. Another line of research has demonstrated - using rate-based neural networks trained with back-propagation - that having many layers increases the recognition robustness, an approach known as deep learning. We thus designed a deep SNN, comprising several convolutional (trainable with STDP) and pooling layers. We used a temporal coding scheme where the most strongly activated neurons fire first, and less activated neurons fire later or not at all. The network was exposed to natural images. Thanks to STDP, neurons progressively learned features corresponding to prototypical patterns that were both salient and frequent. Only a few tens of examples per category were required and no label was needed. After learning, the complexity of the extracted features increased along the hierarchy, from edge detectors in the first layer to object prototypes in the last layer. Coding was very sparse, with only a few thousands spikes per image, and in some cases the object category could be reasonably well inferred from the activity of a single higher-order neuron. More generally, the activity of a few hundreds of such neurons contained robust category information, as demonstrated using a classifier on Caltech 101, ETH-80, and MNIST databases. We also demonstrate the superiority of STDP over other unsupervised techniques such as random crops (HMAX) or auto-encoders. Taken together, our results suggest that the combination of STDP with latency coding may be a key to understanding the way that the primate visual system learns, its remarkable processing speed and its low energy consumption. These mechanisms are also interesting for artificial vision systems, particularly for hardware

Hierarchical Context Modeling for Video Event Recognition.

Science.gov (United States)

Wang, Xiaoyang; Ji, Qiang

2016-10-11

Current video event recognition research remains largely target-centered. For real-world surveillance videos, targetcentered event recognition faces great challenges due to large intra-class target variation, limited image resolution, and poor detection and tracking results. To mitigate these challenges, we introduced a context-augmented video event recognition approach. Specifically, we explicitly capture different types of contexts from three levels including image level, semantic level, and prior level. At the image level, we introduce two types of contextual features including the appearance context features and interaction context features to capture the appearance of context objects and their interactions with the target objects. At the semantic level, we propose a deep model based on deep Boltzmann machine to learn event object representations and their interactions. At the prior level, we utilize two types of prior-level contexts including scene priming and dynamic cueing. Finally, we introduce a hierarchical context model that systematically integrates the contextual information at different levels. Through the hierarchical context model, contexts at different levels jointly contribute to the event recognition. We evaluate the hierarchical context model for event recognition on benchmark surveillance video datasets. Results show that incorporating contexts in each level can improve event recognition performance, and jointly integrating three levels of contexts through our hierarchical model achieves the best performance.

One-single physical exercise session after object recognition learning promotes memory persistence through hippocampal noradrenergic mechanisms.

Science.gov (United States)

da Silva de Vargas, Liane; Neves, Ben-Hur Souto das; Roehrs, Rafael; Izquierdo, Iván; Mello-Carpes, Pâmela

2017-06-30

Previously we showed the involvement of the hippocampal noradrenergic system in the consolidation and persistence of object recognition (OR) memory. Here we show that one-single physical exercise session performed immediately after learning promotes OR memory persistence and increases norepinephrine levels in the hippocampus. Additionally, effects of exercise on memory are avoided by an intra-hippocampal beta-adrenergic antagonist infusion. Taken together, these results suggest that exercise effects on memory can be related to noradrenergic mechanisms and acute physical exercise can be a non-pharmacological intervention to assist memory consolidation and persistence, with few or no side effects. Copyright © 2017 Elsevier B.V. All rights reserved.

Object recognition with video-theodolites and without targeting the object

International Nuclear Information System (INIS)

Kahmen, H.; Seixas, A. de

1999-01-01

At the Department of Applied Geodesy and Engineering Geodesy (TU Vienna) an new kind of theodolite measurement system is under development, enabling measurements with an accuracy of 1:30.000 with and without targeting the object. The main goal is, to develop an intelligent multi-sensor system. Thus an operator is only needed to supervise the system. Results are gained on-sine and can be stored in a CAD system. If no artificial targets are used identification of points has to be performed by the Master-Theodolite. The method, used in our project, is based on interest operators. The Slave-Theodolite has to track the master by searching for homologous regions. The before described method can only be used, if there is some texture on the surface of the object. If that is not fulfilled, a 'grid-line-method' can be used, to get informations about the surface of the object. In the case of a cartesian co-ordinate system, for instance, the grid-lines can be chosen by the operator before the measurement process is started. The theodolite-measurement system is then able to detect the grid-lines and to find the positions where the grid-lines intersect the surface of the object. This system could be used for positioning the different components of a particle accelerator. (author)

Object recognition with video-theodolites and without targeting the object

Energy Technology Data Exchange (ETDEWEB)

Kahmen, H.; Seixas, A. de [University of Technology Vienna, Institute of Geodesy and Geophysics, Vienna (Austria)

1999-07-01

At the Department of Applied Geodesy and Engineering Geodesy (TU Vienna) an new kind of theodolite measurement system is under development, enabling measurements with an accuracy of 1:30.000 with and without targeting the object. The main goal is, to develop an intelligent multi-sensor system. Thus an operator is only needed to supervise the system. Results are gained on-sine and can be stored in a CAD system. If no artificial targets are used identification of points has to be performed by the Master-Theodolite. The method, used in our project, is based on interest operators. The Slave-Theodolite has to track the master by searching for homologous regions. The before described method can only be used, if there is some texture on the surface of the object. If that is not fulfilled, a 'grid-line-method' can be used, to get informations about the surface of the object. In the case of a cartesian co-ordinate system, for instance, the grid-lines can be chosen by the operator before the measurement process is started. The theodolite-measurement system is then able to detect the grid-lines and to find the positions where the grid-lines intersect the surface of the object. This system could be used for positioning the different components of a particle accelerator. (author)

5,7-DHT lesion of the dorsal raphe nuclei impairs object recognition but not affective behavior and corticosterone response to stressor in the rat.

Science.gov (United States)

Lieben, Cindy K J; Steinbusch, Harry W M; Blokland, Arjan

2006-04-03

Previous studies with acute tryptophan depletion, leading to transient central 5-HT reductions, showed no effects on affective behavior but impaired object memory. In the present study, the behavioral effects of a 5,7-dihydroxytryptamine (5,7-DHT) lesion in the dorsal raphe were evaluated in animal models of anxiety (open field test), depression (forced swimming test), behavioral inhibition (discrete fixed interval test) and cognition (object recognition task). The corticosterone response to a stress condition was examined at several intervals after 5,7-DHT treatment. The substantial reduction in neuronal 5-HT markers in the dorsal raphe did not affect anxiety-related, depressive-like or impulsive behavior. Compared to the SHAM group, the lesioned rats showed a lower response latency to obtain a reward, indicating a quick and accurate reaction to a stimulus. No differences were found in the progressive ratio test for food motivation. A marked impairment in object recognition was found. The 5,7-DHT treatment did not affect the corticosterone response to a stressful situation. Overall, these results corroborate studies with acute tryptophan depletion suggesting a role of 5-HT in object memory, but not affective behavior.

Gliding and Saccadic Gaze Gesture Recognition in Real Time

DEFF Research Database (Denmark)

Rozado, David; San Agustin, Javier; Rodriguez, Francisco

2012-01-01

, and their corresponding real-time recognition algorithms, Hierarchical Temporal Memory networks and the Needleman-Wunsch algorithm for sequence alignment. Our results show how a specific combination of gaze gesture modality, namely saccadic gaze gestures, and recognition algorithm, Needleman-Wunsch, allows for reliable...... usage of intentional gaze gestures to interact with a computer with accuracy rates of up to 98% and acceptable completion speed. Furthermore, the gesture recognition engine does not interfere with otherwise standard human-machine gaze interaction generating therefore, very low false positive rates...

The Achievement of Therapeutic Objectives Scale: Interrater Reliability and Sensitivity to Change in Short-Term Dynamic Psychotherapy and Cognitive Therapy

Science.gov (United States)

Valen, Jakob; Ryum, Truls; Svartberg, Martin; Stiles, Tore C.; McCullough, Leigh

2011-01-01

This study examined interrater reliability and sensitivity to change of the Achievement of Therapeutic Objectives Scale (ATOS; McCullough, Larsen, et al., 2003) in short-term dynamic psychotherapy (STDP) and cognitive therapy (CT). The ATOS is a process scale originally developed to assess patients' achievements of treatment objectives in STDP,…

Infants' Recognition of Objects Using Canonical Color

Science.gov (United States)

Kimura, Atsushi; Wada, Yuji; Yang, Jiale; Otsuka, Yumiko; Dan, Ippeita; Masuda, Tomohiro; Kanazawa, So; Yamaguchi, Masami K.

2010-01-01

We explored infants' ability to recognize the canonical colors of daily objects, including two color-specific objects (human face and fruit) and a non-color-specific object (flower), by using a preferential looking technique. A total of 58 infants between 5 and 8 months of age were tested with a stimulus composed of two color pictures of an object…

Sonographic Diagnosis of Tubal Cancer with IOTA Simple Rules Plus Pattern Recognition

Science.gov (United States)

Tongsong, Theera; Wanapirak, Chanane; Tantipalakorn, Charuwan; Tinnangwattana, Dangcheewan

2017-11-26

Objective: To evaluate diagnostic performance of IOTA simple rules plus pattern recognition in predicting tubal cancer. Methods: Secondary analysis was performed on prospective database of our IOTA project. The patients recruited in the project were those who were scheduled for pelvic surgery due to adnexal masses. The patients underwent ultrasound examinations within 24 hours before surgery. On ultrasound examination, the masses were evaluated using the well-established IOTA simple rules plus pattern recognition (sausage-shaped appearance, incomplete septum, visible ipsilateral ovaries) to predict tubal cancer. The gold standard diagnosis was based on histological findings or operative findings. Results: A total of 482 patients, including 15 cases of tubal cancer, were evaluated by ultrasound preoperatively. The IOTA simple rules plus pattern recognition gave a sensitivity of 86.7% (13 in 15) and specificity of 97.4%. Sausage-shaped appearance was identified in nearly all cases (14 in 15). Incomplete septa and normal ovaries could be identified in 33.3% and 40%, respectively. Conclusion: IOTA simple rules plus pattern recognition is relatively effective in predicting tubal cancer. Thus, we propose the simple scheme in diagnosis of tubal cancer as follows. First of all, the adnexal masses are evaluated with IOTA simple rules. If the B-rules could be applied, tubal cancer is reliably excluded. If the M-rules could be applied or the result is inconclusive, careful delineation of the mass with pattern recognition should be performed. Creative Commons Attribution License

Programming Recognition Arrays through Double Chalcogen-Bonding Interactions.

Science.gov (United States)

Biot, Nicolas; Bonifazi, Davide

2018-04-11

In this work, we have programmed and synthesized a recognition motif constructed around a chalcogenazolo-pyridine scaffold (CGP) that, through the formation of frontal double chalcogen-bonding interactions, associates into dimeric EX-type complexes. The reliability of the double chalcogen-bonding interaction has been shown at the solid-state by X-ray analysis, depicting the strongest recognition persistence for a Te-congener. The high recognition fidelity, chemical and thermal stability and easy derivatization at the 2-position makes CGP a convenient motif for constructing supramolecular architectures through programmed chalcogen-bonding interactions. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Objective Prediction of Hearing Aid Benefit Across Listener Groups Using Machine Learning: Speech Recognition Performance With Binaural Noise-Reduction Algorithms

Science.gov (United States)

Schädler, Marc R.; Warzybok, Anna; Kollmeier, Birger

2018-01-01

The simulation framework for auditory discrimination experiments (FADE) was adopted and validated to predict the individual speech-in-noise recognition performance of listeners with normal and impaired hearing with and without a given hearing-aid algorithm. FADE uses a simple automatic speech recognizer (ASR) to estimate the lowest achievable speech reception thresholds (SRTs) from simulated speech recognition experiments in an objective way, independent from any empirical reference data. Empirical data from the literature were used to evaluate the model in terms of predicted SRTs and benefits in SRT with the German matrix sentence recognition test when using eight single- and multichannel binaural noise-reduction algorithms. To allow individual predictions of SRTs in binaural conditions, the model was extended with a simple better ear approach and individualized by taking audiograms into account. In a realistic binaural cafeteria condition, FADE explained about 90% of the variance of the empirical SRTs for a group of normal-hearing listeners and predicted the corresponding benefits with a root-mean-square prediction error of 0.6 dB. This highlights the potential of the approach for the objective assessment of benefits in SRT without prior knowledge about the empirical data. The predictions for the group of listeners with impaired hearing explained 75% of the empirical variance, while the individual predictions explained less than 25%. Possibly, additional individual factors should be considered for more accurate predictions with impaired hearing. A competing talker condition clearly showed one limitation of current ASR technology, as the empirical performance with SRTs lower than −20 dB could not be predicted. PMID:29692200

Under what conditions is recognition spared relative to recall after selective hippocampal damage in humans?

Science.gov (United States)

Holdstock, J S; Mayes, A R; Roberts, N; Cezayirli, E; Isaac, C L; O'Reilly, R C; Norman, K A

2002-01-01

The claim that recognition memory is spared relative to recall after focal hippocampal damage has been disputed in the literature. We examined this claim by investigating object and object-location recall and recognition memory in a patient, YR, who has adult-onset selective hippocampal damage. Our aim was to identify the conditions under which recognition was spared relative to recall in this patient. She showed unimpaired forced-choice object recognition but clearly impaired recall, even when her control subjects found the object recognition task to be numerically harder than the object recall task. However, on two other recognition tests, YR's performance was not relatively spared. First, she was clearly impaired at an equivalently difficult yes/no object recognition task, but only when targets and foils were very similar. Second, YR was clearly impaired at forced-choice recognition of object-location associations. This impairment was also unrelated to difficulty because this task was no more difficult than the forced-choice object recognition task for control subjects. The clear impairment of yes/no, but not of forced-choice, object recognition after focal hippocampal damage, when targets and foils are very similar, is predicted by the neural network-based Complementary Learning Systems model of recognition. This model postulates that recognition is mediated by hippocampally dependent recollection and cortically dependent familiarity; thus hippocampal damage should not impair item familiarity. The model postulates that familiarity is ineffective when very similar targets and foils are shown one at a time and subjects have to identify which items are old (yes/no recognition). In contrast, familiarity is effective in discriminating which of similar targets and foils, seen together, is old (forced-choice recognition). Independent evidence from the remember/know procedure also indicates that YR's familiarity is normal. The Complementary Learning Systems model can

Insular Cortex Is Involved in Consolidation of Object Recognition Memory

Science.gov (United States)

Bermudez-Rattoni, Federico; Okuda, Shoki; Roozendaal, Benno; McGaugh, James L.

2005-01-01

Extensive evidence indicates that the insular cortex (IC), also termed gustatory cortex, is critically involved in conditioned taste aversion and taste recognition memory. Although most studies of the involvement of the IC in memory have investigated taste, there is some evidence that the IC is involved in memory that is not based on taste. In…

Active object recognition using vocabulary trees

CSIR Research Space (South Africa)

Govender, N

2013-01-01

Full Text Available . Using this quantity, a feature’s uniqueness may be cal- culated. This is done in the following way. The feature’s Figure 3. Viewpoint weightings for a spice bottle object in the database. path through the vocabulary tree is determined by evaluat- ing... on the background will not negatively effect the weighting since all images were captured using the same background and their uniqueness weighting will be extremely low. Figure 3 is an example polar plot of viewpoint weightings for a spice bottle object...

High-resolution imaging of expertise reveals reliable object selectivity in the fusiform face area related to perceptual performance.

Science.gov (United States)

McGugin, Rankin Williams; Gatenby, J Christopher; Gore, John C; Gauthier, Isabel

2012-10-16

The fusiform face area (FFA) is a region of human cortex that responds selectively to faces, but whether it supports a more general function relevant for perceptual expertise is debated. Although both faces and objects of expertise engage many brain areas, the FFA remains the focus of the strongest modular claims and the clearest predictions about expertise. Functional MRI studies at standard-resolution (SR-fMRI) have found responses in the FFA for nonface objects of expertise, but high-resolution fMRI (HR-fMRI) in the FFA [Grill-Spector K, et al. (2006) Nat Neurosci 9:1177-1185] and neurophysiology in face patches in the monkey brain [Tsao DY, et al. (2006) Science 311:670-674] reveal no reliable selectivity for objects. It is thus possible that FFA responses to objects with SR-fMRI are a result of spatial blurring of responses from nonface-selective areas, potentially driven by attention to objects of expertise. Using HR-fMRI in two experiments, we provide evidence of reliable responses to cars in the FFA that correlate with behavioral car expertise. Effects of expertise in the FFA for nonface objects cannot be attributed to spatial blurring beyond the scale at which modular claims have been made, and within the lateral fusiform gyrus, they are restricted to a small area (200 mm(2) on the right and 50 mm(2) on the left) centered on the peak of face selectivity. Experience with a category may be sufficient to explain the spatially clustered face selectivity observed in this region.

Evaluation of automatic face recognition for automatic border control on actual data recorded of travellers at Schiphol Airport

NARCIS (Netherlands)

Spreeuwers, Lieuwe Jan; Hendrikse, A.J.; Gerritsen, K.J.; Brömme, A.; Busch, C.

2012-01-01

Automatic border control at airports using automated facial recognition for checking the passport is becoming more and more common. A problem is that it is not clear how reliable these automatic gates are. Very few independent studies exist that assess the reliability of automated facial recognition

Indoor sign recognition for the blind

CSIR Research Space (South Africa)

Kunene, D

2016-09-01

Full Text Available that is faster and more reliable. We first segment the signs by colour, and then by shape recognition. The sign-type classification is done using a tree search structure that enables the use of iterative contour descriptors like the speeded-up-robust features...

Object Recognition via Information-Theoretic Measures/Metrics

National Research Council Canada - National Science Library

Repperger, Daniel W; Pinkus, Alan R; Skipper, Julie A; Schrider, Christian D

2006-01-01

.... In aerial military images, objects with different orientation can be reasonably approximated by a single identification signature consisting of the average histogram of the object under rotations...

Visual object recognition for automatic micropropagation of plants

Science.gov (United States)

Brendel, Thorsten; Schwanke, Joerg; Jensch, Peter F.

1994-11-01

Micropropagation of plants is done by cutting juvenile plants and placing them into special container-boxes with nutrient-solution where the pieces can grow up and be cut again several times. To produce high amounts of biomass it is necessary to do plant micropropagation by a robotic system. In this paper we describe parts of the vision system that recognizes plants and their particular cutting points. Therefore, it is necessary to extract elements of the plants and relations between these elements (for example root, stem, leaf). Different species vary in their morphological appearance, variation is also immanent in plants of the same species. Therefore, we introduce several morphological classes of plants from that we expect same recognition methods.

Modeling recall memory for emotional objects in Alzheimer's disease.

Science.gov (United States)

Sundstrøm, Martin

2011-07-01

To examine whether emotional memory (EM) of objects with self-reference in Alzheimer's disease (AD) can be modeled with binomial logistic regression in a free recall and an object recognition test to predict EM enhancement. Twenty patients with AD and twenty healthy controls were studied. Six objects (three presented as gifts) were shown to each participant. Ten minutes later, a free recall and a recognition test were applied. The recognition test had target-objects mixed with six similar distracter objects. Participants were asked to name any object in the recall test and identify each object in the recognition test as known or unknown. The total of gift objects recalled in AD patients (41.6%) was larger than neutral objects (13.3%) and a significant EM recall effect for gifts was found (Wilcoxon: p recall and recognition but showed no EM enhancement due to a ceiling effect. A logistic regression showed that likelihood of emotional recall memory can be modeled as a function of MMSE score (p Recall memory was enhanced in AD patients for emotional objects indicating that EM in mild to moderate AD although impaired can be provoked with strong emotional load. The logistic regression model suggests that EM declines with the progression of AD rather than disrupts and may be a useful tool for evaluating magnitude of emotional load.

Multi-objective optimization of generalized reliability design problems using feature models-A concept for early design stages

International Nuclear Information System (INIS)

Limbourg, Philipp; Kochs, Hans-Dieter

2008-01-01

Reliability optimization problems such as the redundancy allocation problem (RAP) have been of considerable interest in the past. However, due to the restrictions of the design space formulation, they may not be applicable in all practical design problems. A method with high modelling freedom for rapid design screening is desirable, especially in early design stages. This work presents a novel approach to reliability optimization. Feature modelling, a specification method originating from software engineering, is applied for the fast specification and enumeration of complex design spaces. It is shown how feature models can not only describe arbitrary RAPs but also much more complex design problems. The design screening is accomplished by a multi-objective evolutionary algorithm for probabilistic objectives. Comparing averages or medians may hide the true characteristics of this distributions. Therefore the algorithm uses solely the probability of a system dominating another to achieve the Pareto optimal set. We illustrate the approach by specifying a RAP and a more complex design space and screening them with the evolutionary algorithm

Behavioral model of visual perception and recognition

Science.gov (United States)

Rybak, Ilya A.; Golovan, Alexander V.; Gusakova, Valentina I.

1993-09-01

In the processes of visual perception and recognition human eyes actively select essential information by way of successive fixations at the most informative points of the image. A behavioral program defining a scanpath of the image is formed at the stage of learning (object memorizing) and consists of sequential motor actions, which are shifts of attention from one to another point of fixation, and sensory signals expected to arrive in response to each shift of attention. In the modern view of the problem, invariant object recognition is provided by the following: (1) separated processing of `what' (object features) and `where' (spatial features) information at high levels of the visual system; (2) mechanisms of visual attention using `where' information; (3) representation of `what' information in an object-based frame of reference (OFR). However, most recent models of vision based on OFR have demonstrated the ability of invariant recognition of only simple objects like letters or binary objects without background, i.e. objects to which a frame of reference is easily attached. In contrast, we use not OFR, but a feature-based frame of reference (FFR), connected with the basic feature (edge) at the fixation point. This has provided for our model, the ability for invariant representation of complex objects in gray-level images, but demands realization of behavioral aspects of vision described above. The developed model contains a neural network subsystem of low-level vision which extracts a set of primary features (edges) in each fixation, and high- level subsystem consisting of `what' (Sensory Memory) and `where' (Motor Memory) modules. The resolution of primary features extraction decreases with distances from the point of fixation. FFR provides both the invariant representation of object features in Sensor Memory and shifts of attention in Motor Memory. Object recognition consists in successive recall (from Motor Memory) and execution of shifts of attention and

Test-retest reliability and validity of the Sniffin' TOM odor memory test.

Science.gov (United States)

Croy, Ilona; Zehner, Cora; Larsson, Maria; Zucco, Gesualdo M; Hummel, Thomas

2015-03-01

Few attempts have been made to develop an olfactory test that captures episodic retention of olfactory information. Assessment of episodic odor memory is of particular interest in aging and in the cognitively impaired as both episodic memory deficits and olfactory loss have been targeted as reliable hallmarks of cognitive decline and impending dementia. Here, 96 healthy participants (18-92 years) and an additional 19 older people with mild cognitive impairment were tested (73-82 years). Participants were presented with 8 common odors with intentional encoding instructions that were followed by a yes-no recognition test. After recognition completion, participants were asked to identify all odors by means of free or cued identification. A retest of the odor memory test (Sniffin' TOM = test of odor memory) took place 17 days later. The results revealed satisfactory test-retest reliability (0.70) of odor recognition memory. Both recognition and identification performance were negatively affected by age and more pronounced among the cognitively impaired. In conclusion, the present work presents a reliable, valid, and simple test of episodic odor recognition memory that may be used in clinical groups where both episodic memory deficits and olfactory loss are prevalent preclinically such as Alzheimer's disease. © The Author 2014. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

A method for the evaluation of image quality according to the recognition effectiveness of objects in the optical remote sensing image using machine learning algorithm.

Directory of Open Access Journals (Sweden)

Tao Yuan

Full Text Available Objective and effective image quality assessment (IQA is directly related to the application of optical remote sensing images (ORSI. In this study, a new IQA method of standardizing the target object recognition rate (ORR is presented to reflect quality. First, several quality degradation treatments with high-resolution ORSIs are implemented to model the ORSIs obtained in different imaging conditions; then, a machine learning algorithm is adopted for recognition experiments on a chosen target object to obtain ORRs; finally, a comparison with commonly used IQA indicators was performed to reveal their applicability and limitations. The results showed that the ORR of the original ORSI was calculated to be up to 81.95%, whereas the ORR ratios of the quality-degraded images to the original images were 65.52%, 64.58%, 71.21%, and 73.11%. The results show that these data can more accurately reflect the advantages and disadvantages of different images in object identification and information extraction when compared with conventional digital image assessment indexes. By recognizing the difference in image quality from the application effect perspective, using a machine learning algorithm to extract regional gray scale features of typical objects in the image for analysis, and quantitatively assessing quality of ORSI according to the difference, this method provides a new approach for objective ORSI assessment.

A method for the evaluation of image quality according to the recognition effectiveness of objects in the optical remote sensing image using machine learning algorithm.

Science.gov (United States)

Yuan, Tao; Zheng, Xinqi; Hu, Xuan; Zhou, Wei; Wang, Wei

2014-01-01

Objective and effective image quality assessment (IQA) is directly related to the application of optical remote sensing images (ORSI). In this study, a new IQA method of standardizing the target object recognition rate (ORR) is presented to reflect quality. First, several quality degradation treatments with high-resolution ORSIs are implemented to model the ORSIs obtained in different imaging conditions; then, a machine learning algorithm is adopted for recognition experiments on a chosen target object to obtain ORRs; finally, a comparison with commonly used IQA indicators was performed to reveal their applicability and limitations. The results showed that the ORR of the original ORSI was calculated to be up to 81.95%, whereas the ORR ratios of the quality-degraded images to the original images were 65.52%, 64.58%, 71.21%, and 73.11%. The results show that these data can more accurately reflect the advantages and disadvantages of different images in object identification and information extraction when compared with conventional digital image assessment indexes. By recognizing the difference in image quality from the application effect perspective, using a machine learning algorithm to extract regional gray scale features of typical objects in the image for analysis, and quantitatively assessing quality of ORSI according to the difference, this method provides a new approach for objective ORSI assessment.

Neural circuitry for rat recognition memory

Science.gov (United States)

Warburton, E.C.; Brown, M.W.

2015-01-01

Information concerning the roles of different brain regions in recognition memory processes is reviewed. The review concentrates on findings from spontaneous recognition memory tasks performed by rats, including memory for single objects, locations, object–location associations and temporal order. Particular emphasis is given to the potential roles of different regions in the circuit of interacting structures involving the perirhinal cortex, hippocampus, medial prefrontal cortex and medial dorsal thalamus in recognition memory for the association of objects and places. It is concluded that while all structures in this circuit play roles critical to such memory, these roles can potentially be differentiated and differences in the underlying synaptic and biochemical processes involved in each region are beginning to be uncovered. PMID:25315129

Automated Degradation Diagnosis in Character Recognition System Subject to Camera Vibration

Directory of Open Access Journals (Sweden)

Chunmei Liu

2014-01-01

Full Text Available Degradation diagnosis plays an important role for degraded character processing, which can tell the recognition difficulty of a given degraded character. In this paper, we present a framework for automated degraded character recognition system by statistical syntactic approach using 3D primitive symbol, which is integrated by degradation diagnosis to provide accurate and reliable recognition results. Our contribution is to design the framework to build the character recognition submodels corresponding to degradation subject to camera vibration or out of focus. In each character recognition submodel, statistical syntactic approach using 3D primitive symbol is proposed to improve degraded character recognition performance. In the experiments, we show attractive experimental results, highlighting the system efficiency and recognition performance by statistical syntactic approach using 3D primitive symbol on the degraded character dataset.

Simultaneous tracking and activity recognition

DEFF Research Database (Denmark)

Manfredotti, Cristina Elena; Fleet, David J.; Hamilton, Howard J.

2011-01-01

be used to improve the prediction step of the tracking, while, at the same time, tracking information can be used for online activity recognition. Experimental results in two different settings show that our approach 1) decreases the error rate and improves the identity maintenance of the positional......Many tracking problems involve several distinct objects interacting with each other. We develop a framework that takes into account interactions between objects allowing the recognition of complex activities. In contrast to classic approaches that consider distinct phases of tracking and activity...... tracking and 2) identifies the correct activity with higher accuracy than standard approaches....

Object recognition by implicit invariants

Czech Academy of Sciences Publication Activity Database

Flusser, Jan; Kautsky, J.; Šroubek, Filip

2007-01-01

Roč. 2007, č. 4673 (2007), s. 856-863 ISSN 0302-9743. [Computer Analysis of Images and Patterns. Vienna, 27.08.2007-29.08.2007] R&D Projects: GA MŠk 1M0572 Institutional research plan: CEZ:AV0Z10750506 Keywords : Invariants * implicit invariants * moments * orthogonal polynomials * nonlinear object deformation Subject RIV: JD - Computer Applications, Robotics Impact factor: 0.402, year: 2005 http:// staff .utia.cas.cz/sroubekf/papers/CAIP_07.pdf

HWDA: A coherence recognition and resolution algorithm for hybrid web data aggregation

Science.gov (United States)

Guo, Shuhang; Wang, Jian; Wang, Tong

2017-09-01

Aiming at the object confliction recognition and resolution problem for hybrid distributed data stream aggregation, a distributed data stream object coherence solution technology is proposed. Firstly, the framework was defined for the object coherence conflict recognition and resolution, named HWDA. Secondly, an object coherence recognition technology was proposed based on formal language description logic and hierarchical dependency relationship between logic rules. Thirdly, a conflict traversal recognition algorithm was proposed based on the defined dependency graph. Next, the conflict resolution technology was prompted based on resolution pattern matching including the definition of the three types of conflict, conflict resolution matching pattern and arbitration resolution method. At last, the experiment use two kinds of web test data sets to validate the effect of application utilizing the conflict recognition and resolution technology of HWDA.

Places in the Brain: Bridging Layout and Object Geometry in Scene-Selective Cortex.

Science.gov (United States)

Dillon, Moira R; Persichetti, Andrew S; Spelke, Elizabeth S; Dilks, Daniel D

2017-06-13

Diverse animal species primarily rely on sense (left-right) and egocentric distance (proximal-distal) when navigating the environment. Recent neuroimaging studies with human adults show that this information is represented in 2 scene-selective cortical regions-the occipital place area (OPA) and retrosplenial complex (RSC)-but not in a third scene-selective region-the parahippocampal place area (PPA). What geometric properties, then, does the PPA represent, and what is its role in scene processing? Here we hypothesize that the PPA represents relative length and angle, the geometric properties classically associated with object recognition, but only in the context of large extended surfaces that compose the layout of a scene. Using functional magnetic resonance imaging adaptation, we found that the PPA is indeed sensitive to relative length and angle changes in pictures of scenes, but not pictures of objects that reliably elicited responses to the same geometric changes in object-selective cortical regions. Moreover, we found that the OPA is also sensitive to such changes, while the RSC is tolerant to such changes. Thus, the geometric information typically associated with object recognition is also used during some aspects of scene processing. These findings provide evidence that scene-selective cortex differentially represents the geometric properties guiding navigation versus scene categorization. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

The "general recognition and acceptance" standard of objectivity for good faith in prescribing: legal and medical implications.

Science.gov (United States)

Brushwood, David B

2007-01-01

The United States Court of Appeals for the 4th Circuit has ruled that a jury considering charges of drug trafficking against a pain management physician should be instructed that the defendant's good faith is a defense to the charges. The court rejected a subjective standard of good faith, and instead ruled that the good faith of the defendant must be evaluated from an objective perspective. This objective standard requires that the jury determine whether the defendant was practicing in accordance with the standard generally recognized and accepted in the United States. General recognition and acceptance are determined on a case-by-case basis, within the context of a defendant's practice. Simply because a physician's practice is out of the norm for many physicians does not mean it can't be generally recognized and accepted within the standard of medical practice. Expert witness testimony of pain management physicians will assist juries in the application of this standard for good faith in prescribing.