Download or read book Neural Network Models of Attentive Visual Search and Object Recognition written by William D. Ross and published by . This book was released on 1994 with total page 288 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Biologically based Interactive Neural Network Models for Visual Attention and Object Recognition written by Mohammad Saifullah and published by . This book was released on 2012 with total page 200 pages. Available in PDF, EPUB and Kindle. Book excerpt: The main focus of this thesis is to develop biologically-based computational models for object recognition. A series of models for attention and object recognition were developed in the order of increasing functionality and complexity. These models are based on information processing in the primate brain, and specially inspired from the theory of visual information processing along the two parallel processing pathways of the primate visual cortex. To capture the true essence of incremental, constraint satisfaction style processing in the visual system, interactive neural networks were used for implementing our models. Results from eye-tracking studies on the relevant visual tasks, as well as our hypothesis regarding the information processing in the primate visual system, were implemented in the models and tested with simulations. As a first step, a model based on the ventral pathway was developed to recognize single objects. Through systematic testing, structural and algorithmic parameters of these models were fine tuned for performing their task optimally. In the second step, the model was extended by considering the dorsal pathway, which enables simulation of visual attention as an emergent phenomenon. The extended model was then investigated for visual search tasks. In the last step, we focussed on occluded and overlapped object recognition. A couple of eye-tracking studies were conducted in this regard and on the basis of the results we made some hypotheses regarding information processing in the primate visual system. The models were further advanced on the lines of the presented hypothesis, and simulated on the tasks of occluded and overlapped object recognition. On the basis of the results and analysis of our simulations we have further found that the generalization performance of interactive hierarchical networks improves with the addition of a small amount of Hebbian learning to an otherwise pure error-driven learning. We also concluded that the size of the receptive fields in our networks is an important parameter for the generalization task and depends on the object of interest in the image. Our results show that networks using hard coded feature extraction perform better than the networks that use Hebbian learning for developing feature detectors. We have successfully demonstrated the emergence of visual attention within an interactive network and also the role of context in the search task. Simulation results with occluded and overlapped objects support our extended interactive processing approach, which is a combination of the interactive and top-down approach, to the segmentation-recognition issue. Furthermore, the simulation behavior of our models is in line with known human behavior for similar tasks. In general, the work in this thesis will improve the understanding and performance of biologically-based interactive networks for object recognition and provide a biologically-plausible solution to recognition of occluded and overlapped objects. Moreover, our models provide some suggestions for the underlying neural mechanism and strategies behind biological object recognition.
Download or read book The Attentive Brain written by Raja Parasuraman and published by MIT Press. This book was released on 2000 with total page 622 pages. Available in PDF, EPUB and Kindle. Book excerpt: Of the myriad tasks that the brain has to perform, perhaps none is as crucial to the performance of other tasks as attention. A central thesis of this book on the cognitive neuroscience of attention is that attention is not a single entity, but a finite set of brain processes that interact mutually and with other brain processes in the performance of perceptual, cognitive, and motor skills.After an introductory part I, the book consists of three parts. Part II, Methods, describes the major neuroscience methods, including techniques used only with animals (anatomical tract tracing, single-unit electrophysiology, neurochemical manipulations), noninvasive human brain-imaging techniques (ERPs, positron emission tomography, and functional magnetic resonance imaging), and studies with brain-damaged individuals. This part also includes a chapter on the computational modeling of attention. Part III, Varieties of Attention, looks at three major components of attention from the cognitive neuroscience perspective: selection, vigilance, and control. It also discusses links to memory and language. Finally, part IV, Development and Pathologies, discusses the application of findings from the previous sections to the analysis of normal and abnormal development and to pathologies of attention such as schizophrenia and attention deficit disorders. Contributors Edward Awh, Gordon C. Baylis, Jochen Braun, Dennis Cantwell, Vincent P. Clark, Maurizio Corbetta, Susan M. Courtney, Francis Crinella, Matthew C. Davidson, Gregory J. DiGirolamo, Jon Driver, Jane Emerson, Pauline Filipek, Ira Fischler, Massimo Girelli, Pamela M. Greenwood, James V. Haxby, Mark H. Johnson, John Jonides, Julian S. Joseph, Robert T. Knight, Christof Koch, Steven J. Luck, Richard T. Marrocco, Brad C. Motter, Ken Nakayama, Orhan Nalcioglu, Paul G. Nestor, Ernst Niebur, Brian F. O'Donnell, Raja Parasuraman, Michael I. Posner, Robert D. Rafal, Trevor W. Robbins, Lynn C. Robertson, Judi E. See, James Swanson, Diane Swick, Don Tucker, Leslie G. Ungerleider, Joel S. Warm, Maree J. Webster, Sharon Wigal
Download or read book Neural Models of Multi scale Image Completion and of Featural Bias During Attentive Memory Search written by Sai Chaitanya Gaddam and published by . This book was released on 2009 with total page 288 pages. Available in PDF, EPUB and Kindle. Book excerpt: Abstract: This dissertation develops neural network models for vision and recognition, and tests model performance on large-scale images. The first project introduces CONFIGR (CONtour FIgure GRound), a computational model based on principles of biological vision. Within an integrated vision/recognition system, CONFIGR posits an initial recognition stage which identifies figure pixels from spatially local input information. The resulting figure is fed back to the "early vision" stage for long-range completion via filling-in. In the CONFIGR algorithm, the smallest independent image unit is the visible pixel. Once the pixel size is fixed, the entire algorithm is fully determined, with no additional parameter choices. Multi-scale simulations illustrate the vision/recognition system. The model balances filling-in as figure against complementary filling-in as ground, which blocks spurious figure completions. Originally designed to fill-in missing contours in an incomplete image such as a dashed line, the same CONFIGR system connects sparse dots, and unifies occluded objects from pieces locally identified as figure in the initial recognition stage. The model self-scales its completion distances, filling-in across gaps of any length, where unimpeded, while limiting connections among dense image-figure pixel groups that already have intrinsic form. Long-range image completion promises to play an important role in adaptive processors that reconstruct images from highly compressed video and still camera images. The second project considers a problem faced by online learning systems, which may be presented with input patterns only once during training. In this situation, later training may be distorted by undue attention to initial subsets of features that were useful for earlier memory encoding. During learning, Adaptive Resonance Theory (ART) models encode attended featural subsets, called critical feature patterns. When a novel input activates an established category, only the input features present in the critical pattern remain active in working memory. Biased ARTMAP (bARTMAP) is a neural network that solves the problem of over-emphasis on early features by biasing attention away from previously attended features once an input has made a predictive error. Simulations on a variety of benchmark problems demonstrate that adding biasing to ARTMAP search improves recognition accuracy.
Download or read book VOCUS A Visual Attention System for Object Detection and Goal Directed Search written by Simone Frintrop and published by Springer. This book was released on 2006-03-28 with total page 219 pages. Available in PDF, EPUB and Kindle. Book excerpt: This monograph presents a complete computational system for visual attention and object detection. VOCUS (Visual Object detection with a Computational attention System) represents a major step forward on integrating data-driven and model-driven information into a single framework. Additionally, the volume contains an extensive review of the literature on visual attention, detailed evaluations of VOCUS in different settings, and applications of the system.
Download or read book Attention in Cognitive Systems Theories and Systems from an Interdisciplinary Viewpoint written by Lucas Paletta and published by Springer. This book was released on 2007-12-03 with total page 507 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume provides a much-needed interdisciplinary angle on the subject of attention in cognitive systems. It constitutes the thoroughly refereed post-workshop proceedings of the 5th International Workshop on Attention in Cognitive Systems, held in Hyderabad, India, in January 2007. The 31 papers are organized in topical sections that cover every aspect of the subject, from the embodiment of attention and its cognitive control, to the applications of attentive vision.
Download or read book Biologically Motivated Computer Vision written by Heinrich H. Bülthoff and published by Springer. This book was released on 2003-08-02 with total page 676 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the Second International Workshop on Biologically Motivated Computer Vision, BMCV 2002, held in Tübingen, Germany, in November 2002. The 22 revised full papers and 37 revised short papers presented together with 6 invited papers were carefully reviewed and selected from 97 submissions. The papers are organized in topical sections on neurons and features, motion, mid-level vision, recognition - from scenes to neurons, attention, robotics, and cognitive vision.
Download or read book Attention written by Harold Pashler and published by Psychology Press. This book was released on 2016-01-28 with total page 416 pages. Available in PDF, EPUB and Kindle. Book excerpt: This collection of essays, intended as a text for students, examines the different facets of research into attention. The book is divided into two sections: one deals with psychological research into such areas as visual search, dual-task interference and attentional bottleneck; the other deals with approaches to neural-network modelling and the effects of brain damage on attention.
Download or read book Innovative Research in Attention Modeling and Computer Vision Applications written by Pal, Rajarshi and published by IGI Global. This book was released on 2015-10-02 with total page 475 pages. Available in PDF, EPUB and Kindle. Book excerpt: Robotics and autonomous systems can aid disabled individuals in daily living or make a workplace more productive, but these tools are only as effective as the technology behind them. Robotic systems must be able to accurately identify and act upon elements in their environment to be effective in performing their duties. Innovative Research in Attention Modeling and Computer Vision Applications explores the latest research in image processing and pattern recognition for use in robotic real-time cryptography and surveillance applications. This book provides researchers, students, academicians, software designers, and application developers with next-generation insight into the use of computer vision technologies in a variety of industries and endeavors. This premier reference work includes chapters on topics ranging from biometric and facial recognition technologies, to digital image and video watermarking, among many others.
Download or read book Vision Models For Target Detection And Recognition In Memory Of Arthur Menendez written by Eli Peli and published by World Scientific. This book was released on 1995-05-31 with total page 439 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is an international collection of contributions from academia, industry and the armed forces. It addresses current and emerging Spatial Vision Models and their application to the understanding, prediction and evaluation of the tasks of target detection and recognition. The discussion in many of the chapters is framed in terms of military targets and military vision aids. However, the techniques analyses and problems are by no means limited to this area of application. The detection and recognition of an armored vehicle from a reconnaissance image are performed by the same visual system used to detect and recognize a tumor in an X-ray. The analysis of the interaction of the human visual system with night vision devices is not different from the analysis needed in the case of an operator examining structures using a remote (endoscopic) camera, etc. The book is organized into three general sections. The first covers basic modeling of central (foveal) vision and its theoretical background. The second is centered on the evaluation of model performance in applications, while the third is dedicated to aspects of peripheral vision modeling and the expansion of peripheral modeling to include visual search.
Download or read book Object Detection with Deep Learning Models written by S Poonkuntran and published by CRC Press. This book was released on 2022-11-01 with total page 345 pages. Available in PDF, EPUB and Kindle. Book excerpt: Object Detection with Deep Learning Models discusses recent advances in object detection and recognition using deep learning methods, which have achieved great success in the field of computer vision and image processing. It provides a systematic and methodical overview of the latest developments in deep learning theory and its applications to computer vision, illustrating them using key topics, including object detection, face analysis, 3D object recognition, and image retrieval. The book offers a rich blend of theory and practice. It is suitable for students, researchers and practitioners interested in deep learning, computer vision and beyond and can also be used as a reference book. The comprehensive comparison of various deep-learning applications helps readers with a basic understanding of machine learning and calculus grasp the theories and inspires applications in other computer vision tasks. Features: A structured overview of deep learning in object detection A diversified collection of applications of object detection using deep neural networks Emphasize agriculture and remote sensing domains Exclusive discussion on moving object detection
Download or read book Visual Object Tracking with Deep Neural Networks written by Pier Luigi Mazzeo and published by BoD – Books on Demand. This book was released on 2019-12-18 with total page 208 pages. Available in PDF, EPUB and Kindle. Book excerpt: Visual object tracking (VOT) and face recognition (FR) are essential tasks in computer vision with various real-world applications including human-computer interaction, autonomous vehicles, robotics, motion-based recognition, video indexing, surveillance and security. This book presents the state-of-the-art and new algorithms, methods, and systems of these research fields by using deep learning. It is organized into nine chapters across three sections. Section I discusses object detection and tracking ideas and algorithms; Section II examines applications based on re-identification challenges; and Section III presents applications based on FR research.
Download or read book Visual Attention Mechanisms written by Virginio Cantoni and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 283 pages. Available in PDF, EPUB and Kindle. Book excerpt: Proceedings of the Fifth International School on Neural Networks "E.R. Caianiello" on Visual Attention MechaProceedings of the Fifth International School on Neural Networks "E.R. Caianiello" on Visual Attention Mechanisms, held 23-28 October 2000 in Vietri sul Mare, Italy.nisms, held 23-28 October 2000 in Vietri sul Mare, Italy. The book covers a number of broad themes relevant to visual attention, ranging from computer vision to psychology and physiology of vision. The main theme of the book is the attention processes of vision systems and it aims to point out the analogies and the divergences of biological vision with the frameworks introduced by computer scientists in artificial vision.
Download or read book Hierarchical Object Representations in the Visual Cortex and Computer Vision written by Antonio Rodríguez-Sánchez and published by Frontiers Media SA. This book was released on 2016-06-08 with total page 292 pages. Available in PDF, EPUB and Kindle. Book excerpt: Over the past 40 years, neurobiology and computational neuroscience has proved that deeper understanding of visual processes in humans and non-human primates can lead to important advancements in computational perception theories and systems. One of the main difficulties that arises when designing automatic vision systems is developing a mechanism that can recognize - or simply find - an object when faced with all the possible variations that may occur in a natural scene, with the ease of the primate visual system. The area of the brain in primates that is dedicated at analyzing visual information is the visual cortex. The visual cortex performs a wide variety of complex tasks by means of simple operations. These seemingly simple operations are applied to several layers of neurons organized into a hierarchy, the layers representing increasingly complex, abstract intermediate processing stages. In this Research Topic we propose to bring together current efforts in neurophysiology and computer vision in order 1) To understand how the visual cortex encodes an object from a starting point where neurons respond to lines, bars or edges to the representation of an object at the top of the hierarchy that is invariant to illumination, size, location, viewpoint, rotation and robust to occlusions and clutter; and 2) How the design of automatic vision systems benefit from that knowledge to get closer to human accuracy, efficiency and robustness to variations.
Download or read book Handbook of Neural Computation written by Emile Fiesler and published by CRC Press. This book was released on 1997-01-01 with total page 120 pages. Available in PDF, EPUB and Kindle. Book excerpt: In recent years, neural computation has developed from a specialized research discipline into a broadly based and dynamic activity with applications in an astonishing variety of fields. Many scientists, engineers and other practitioners are now using neural networks to tackle problems that are either intractable or unrealistically time consuming to solve through traditional computational strategies. The inaugural volume in the Computational Intelligence Library provides speedy dissemination of new ideas to a broad spectrum of neural network users, designers and implementers. Devoted to network fundamentals, models, algorithms and applications, the work is intended to become the standard reference resource for the neural network community. As the field expands and develops, leading researchers will report on an analyze promising new approaches. In this way, the Handbook will become an evolving compendium on the state of the art of neural computation. Available in loose-leaf print form as well as in an electronic edition that combines both CD-ROM and on-line (World Wide Web) access to its contents, the Handbook of Neural Computation is available on a subscription basis, with regularly published supplements keeping readers abreast of late-breaking developments and new advances in this rapidly developing field.
Download or read book Neurobiology of Attention written by Laurent Itti and published by Elsevier. This book was released on 2005-03-31 with total page 757 pages. Available in PDF, EPUB and Kindle. Book excerpt: A key property of neural processing in higher mammals is the ability to focus resources by selectively directing attention to relevant perceptions, thoughts or actions. Research into attention has grown rapidly over the past two decades, as new techniques have become available to study higher brain function in humans, non-human primates, and other mammals. Neurobiology of Attention is the first encyclopedic volume to summarize the latest developments in attention research.An authoritative collection of over 100 chapters organized into thematic sections provides both broad coverage and access to focused, up-to-date research findings. This book presents a state-of-the-art multidisciplinary perspective on psychological, physiological and computational approaches to understanding the neurobiology of attention. Ideal for students, as a reference handbook or for rapid browsing, the book has a wide appeal to anybody interested in attention research.* Contains numerous quick-reference articles covering the breadth of investigation into the subject of attention* Provides extensive introductory commentary to orient and guide the reader* Includes the most recent research results in this field of study
Download or read book Stevens Handbook of Experimental Psychology and Cognitive Neuroscience Set written by John T. Wixted and published by Wiley. This book was released on 2018-04-10 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Since the first edition was published in 1951, The Stevens' Handbook of Experimental Psychology has been recognized as the standard reference in the field. The most recent (3rd) edition of the handbook was published in 2004, and it was a success by any measure. But the field of experimental psychology has changed in dramatic ways since then. Throughout the first 3 editions of the handbook, the changes in the field were mainly quantitative in nature. That is, the size and scope of the field grew steadily from 1951 to 2004, a trend that was reflected in the growing size of the handbook itself: the 1-volume first edition (1951) was succeeded by a 2-volume second edition (1988) and then by a 4-volume third edition (2004). Since 2004, however, this still-growing field has also changed qualitatively in the sense that, in virtually every subdomain of experimental psychology, theories of the mind have evolved into theories of the brain. Research methods in experimental psychology have changed accordingly and now include not only venerable EEG recordings (long a staple of research in psycholinguistics) but also MEG, fMRI, TMS, and single-unit recording. The trend towards neuroscience is an absolutely dramatic, worldwide phenomenon that is unlikely to ever be reversed. Thus, the era of purely behavioral experimental psychology is already long gone, even though not everyone has noticed. Experimental psychology and "cognitive neuroscience" (an umbrella term that includes behavioral neuroscience, social neuroscience and developmental neuroscience) are now inextricably intertwined. Nearly every major psychology department in the country has added cognitive neuroscientists to its ranks in recent years, and that trend is still growing. A viable handbook of experimental psychology should reflect the new reality on the ground. There is no handbook in existence today that combines basic experimental psychology and cognitive neuroscience, this despite the fact that the two fields are interrelated – and even interdependent – because they are concerned with the same issues (e.g., memory, perception, language, development, etc.). Almost all neuroscience-oriented research takes as its starting point what has been learned using behavioral methods in experimental psychology. In addition, nowadays, psychological theories increasingly take into account what has been learned about the brain (e.g., psychological models increasingly need to be neurologically plausible). These considerations explain why this edition of: The Stevens' Handbook of Experimental Psychology is now called The Stevens' Handbook of Experimental Psychology and Cognitive Neuroscience. The title serves as a reminder that the two fields go together and as an announcement that the Stevens' Handbook covers it all. The 4th edition of the Stevens’ Handbook is a 5-volume set structured as follows: I. Learning & Memory: Elizabeth Phelps & Lila Davachi (Volume Editors) Topics include fear learning; time perception; working memory; visual object recognition; memory and future imagining; sleep and memory; emotion and memory; attention and memory; motivation and memory; inhibition in memory; education and memory; aging and memory; autobiographical memory; eyewitness memory; and category learning. II. Sensation, Perception & Attention: John Serences (Volume Editor) Topics include attention; vision; color vision; visual search; depth perception; taste; touch; olfaction; motor control; perceptual learning; audition; music perception; multisensory integration; vestibular, proprioceptive, and haptic contributions to spatial orientation; motion perception; perceptual rhythms; the interface theory of perception; perceptual organization; perception and interactive technology; perception for action. III. Language & Thought: Sharon Thompson-Schill (Volume Editor) Topics include reading; discourse and dialogue; speech production; sentence processing; bilingualism; concepts and categorization; culture and cognition; embodied cognition; creativity; reasoning; speech perception; spatial cognition; word processing; semantic memory; moral reasoning. IV. Developmental & Social Psychology: Simona Ghetti (Volume Editor) Topics include development of visual attention; self-evaluation; moral development; emotion-cognition interactions; person perception; memory; implicit social cognition; motivation group processes; development of scientific thinking; language acquisition; category and conceptual development; development of mathematical reasoning; emotion regulation; emotional development; development of theory of mind; attitudes; executive function. V. Methodology: E. J. Wagenmakers (Volume Editor) Topics include hypothesis testing and statistical inference; model comparison in psychology; mathematical modeling in cognition and cognitive neuroscience; methods and models in categorization; serial versus parallel processing; theories for discriminating signal from noise; Bayesian cognitive modeling; response time modeling; neural networks and neurocomputational modeling; methods in psychophysics analyzing neural time series data; convergent methods of memory research; models and methods for reinforcement learning; cultural consensus theory; network models for clinical psychology; the stop-signal paradigm; fmri; neural recordings; open science.
