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Map-Seeking Circuits in Visual Cognition

Map-Seeking Circuits in Visual Cognition
Author: David W. Arathorn
Publisher: Stanford University Press
Total Pages: 252
Release: 2002
Genre: Science
ISBN: 9780804742771

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This work presents a bold new theory of the cognitive circuitry of the brain, with emphasis on the functioning of human vision. Departing from conventional precepts in the fields of artificial intelligence, neuroscience, and visual psychophysics, the author has developed a computational theory that provides a unitary explanation for a wide range of visual capabilities and behaviors, most of which have no accepted theoretical explanation. He describes a cortical mechanism termed "map-seeking” and demonstrates its explanatory power in areas as diverse as limb-motion planning and perceptual deficits associated with schizophrenia. The author argues that map-seeking is a fundamental, broadly applicable computational operation with algorithmic, neuronal, and analog electronic implementations, and that its generality makes it suitable as the core of a computational explanation for several cognitive functions. Variations of this map-seeking circuit perform recognition under visual transformations, tracking, scene segmentation, and determination of shape from view displacement. The mathematical principle on which map-seeking depends, a superposition ordering property, solves the combinatorial explosion problem that has plagued all other approaches to visual computation. The author demonstrates that map-seeking is capable of realistic performances in neuronal form and in many current technological procedures. Because of its breadth of application, it is a plausible cortical theory. Because it can be implemented electronically, it forms the basis for a computational technology highly suited for visual, and other perceptual, cognitive, and motor applications.


Analysis of Constrained Optimization Variants of the Map-Seeking Circuit Algorithm

Analysis of Constrained Optimization Variants of the Map-Seeking Circuit Algorithm
Author: C. R. Vogel
Publisher:
Total Pages:
Release: 2005
Genre:
ISBN:

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The map-seeking circuit algorithm (MSC) was developed by Arathorn to efficiently solve the combinatorial problem of correspondence maximization, which arises in applications like computer vision, motion estimation, image matching, and automatic speech recognition [D.W. Arathorn, Map-Seeking Circuits in Visual Cognition: A Computational Mechanism for Biological and Machine Vision, Stanford University Press, 2002]. Given an input image, a template image, and a discrete set of transformations, the goal is to find a composition of transformations which gives the best fit between the transformed input and the template. We imbed the associated combinatorial search problem within a continuous framework by using superposition, and we analyze a resulting constrained optimization problem. We present several numerical schemes to compute local solutions, and we compare their performance on a pair of test problems: an image matching problem and the challenging problem of automatically solving a Rubik's cube.


Neurobiology of Attention

Neurobiology of Attention
Author: Laurent Itti
Publisher: Elsevier
Total Pages: 757
Release: 2005-03-31
Genre: Psychology
ISBN: 0080454313

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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


Information Routing, Correspondence Finding, and Object Recognition in the Brain

Information Routing, Correspondence Finding, and Object Recognition in the Brain
Author: Philipp Wolfrum
Publisher: Springer
Total Pages: 147
Release: 2010-09-07
Genre: Technology & Engineering
ISBN: 3642152546

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At?rstsight,thisbookisaboutfacerecognitioninthebrain.Itsmorelasting value, however,lies in the paradigmatic way in which this particular problem is treated. From the basic ideas that are worked out here in concrete detail, it is a naturaland simple next step to at leastimagine, if not realizein model form, much more generalstructures and processes,thus helping to bridge the still tremendous chasm between mind and brain. It is the purpose of this foreword to point out these generic traits. For centuries, thinking about the brain has been dominated by the most complexmechanisticdevicesofthetime,clockwork,communicatinghydraulic tubesor,today,thecomputer.Thecomputer,takenasincarnationoftheU- versal Turing Machine, can implement any conceivable process, so that also a functional brain can surely be simulated on it, an idea that, beginning in the ?fties of the last century, has been seducing scientists to create “art- cial intelligence” in the computer. As a result we now have an information technology that displays many functional capabilities formerly regarded as the exclusive domain of the mind. As fascinating as this is, doting on “int- ligent machines” is systematically diverting our attention awayfrom the true problems of understanding the working of the brain.


The New Visual Neurosciences

The New Visual Neurosciences
Author: John S. Werner
Publisher: MIT Press
Total Pages: 1693
Release: 2013-10-25
Genre: Science
ISBN: 0262019167

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A comprehensive review of contemporary research in the vision sciences, reflecting the rapid advances of recent years. Visual science is the model system for neuroscience, its findings relevant to all other areas. This essential reference to contemporary visual neuroscience covers the extraordinary range of the field today, from molecules and cell assemblies to systems and therapies. It provides a state-of-the art companion to the earlier book The Visual Neurosciences (MIT Press, 2003). This volume covers the dramatic advances made in the last decade, offering new topics, new authors, and new chapters. The New Visual Neurosciences assembles groundbreaking research, written by international authorities. Many of the 112 chapters treat seminal topics not included in the earlier book. These new topics include retinal feature detection; cortical connectomics; new approaches to mid-level vision and spatiotemporal perception; the latest understanding of how multimodal integration contributes to visual perception; new theoretical work on the role of neural oscillations in information processing; and new molecular and genetic techniques for understanding visual system development. An entirely new section covers invertebrate vision, reflecting the importance of this research in understanding fundamental principles of visual processing. Another new section treats translational visual neuroscience, covering recent progress in novel treatment modalities for optic nerve disorders, macular degeneration, and retinal cell replacement. The New Visual Neurosciences is an indispensable reference for students, teachers, researchers, clinicians, and anyone interested in contemporary neuroscience. Associate Editors Marie Burns, Joy Geng, Mark Goldman, James Handa, Andrew Ishida, George R. Mangun, Kimberley McAllister, Bruno Olshausen, Gregg Recanzone, Mandyam Srinivasan, W.Martin Usrey, Michael Webster, David Whitney Sections Retinal Mechanisms and Processes Organization of Visual Pathways Subcortical Processing Processing in Primary Visual Cortex Brightness and Color Pattern, Surface, and Shape Objects and Scenes Time, Motion, and Depth Eye Movements Cortical Mechanisms of Attention, Cognition, and Multimodal Integration Invertebrate Vision Theoretical Perspectives Molecular and Developmental Processes Translational Visual Neuroscience


Handbook of Pattern Recognition and Computer Vision

Handbook of Pattern Recognition and Computer Vision
Author: Chi-hau Chen
Publisher: World Scientific
Total Pages: 797
Release: 2010
Genre: Computers
ISBN: 9814273384

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Both pattern recognition and computer vision have experienced rapid progress in the last twenty-five years. This book provides the latest advances on pattern recognition and computer vision along with their many applications. It features articles written by renowned leaders in the field while topics are presented in readable form to a wide range of readers. The book is divided into five parts: basic methods in pattern recognition, basic methods in computer vision and image processing, recognition applications, life science and human identification, and systems and technology. There are eight new chapters on the latest developments in life sciences using pattern recognition as well as two new chapters on pattern recognition in remote sensing.


Artificial Neural Networks - ICANN 2008

Artificial Neural Networks - ICANN 2008
Author: Vera Kurkova-Pohlova
Publisher: Springer
Total Pages: 1053
Release: 2008-09-08
Genre: Computers
ISBN: 3540875360

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This two volume set LNCS 5163 and LNCS 5164 constitutes the refereed proceedings of the 18th International Conference on Artificial Neural Networks, ICANN 2008, held in Prague Czech Republic, in September 2008. The 200 revised full papers presented were carefully reviewed and selected from more than 300 submissions. The first volume contains papers on mathematical theory of neurocomputing, learning algorithms, kernel methods, statistical learning and ensemble techniques, support vector machines, reinforcement learning, evolutionary computing, hybrid systems, self-organization, control and robotics, signal and time series processing and image processing.


Artificial General Intelligence, 2008

Artificial General Intelligence, 2008
Author: Pei Wang
Publisher: IOS Press
Total Pages: 520
Release: 2008
Genre: Computers
ISBN: 1586038338

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Includes full-length papers, short position statements and also the papers presented in the post conference workshop on the sociocultural, ethical and futurological implications of Artificial General Intelligence (AGI).


Invariant Recognition of Visual Objects

Invariant Recognition of Visual Objects
Author: Evgeniy Bart
Publisher: Frontiers E-books
Total Pages: 195
Release:
Genre:
ISBN: 2889190765

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This Research Topic will focus on how the visual system recognizes objects regardless of variations in the viewpoint, illumination, retinal size, background, etc. Contributors are encouraged to submit articles describing novel results, models, viewpoints, perspectives and/or methodological innovations relevant to this topic. The issues we wish to cover include, but are not limited to, perceptual invariance under one or more of the following types of image variation: • Object shape • Task • Viewpoint (from the translation and rotation of the object relative to the viewer) • Illumination, shading, and shadows • Degree of occlusion • Retinal size • Color • Surface texture • Visual context, including background clutter and crowding • Object motion (including biological motion). Examples of questions that are particularly interesting in this context include, but are not limited to: • Empirical characterizations of properties of invariance: does invariance always exist? How wide is its range and how strong is the tolerance to viewing conditions within this range? • Invariance in naïve vs. experienced subjects: Is invariance built-in or learned? How can it be learned, under which conditions and how effectively? Is it learned incidentally, or are specific task and reward structures necessary for learning? How is generalizability and transfer of learning related to the generalizability/invariance of perception? • Invariance during inference: Are there conditions (e.g. fast presentation time or otherwise resource-constrained recognition) when invariance breaks? • What are some plausible computational or neural mechanisms by which invariance could be achieved?


Author:
Publisher: IOS Press
Total Pages: 4947
Release:
Genre:
ISBN:

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