Download or read book Computational Models of Early Visual Processing Layers written by Honghao Shan and published by . This book was released on 2010 with total page 160 pages. Available in PDF, EPUB and Kindle. Book excerpt: Visual information passes through layers of processing along the visual pathway, such as retina, lateral geniculate nucleus (LGN), primary visual cortex (V1), prestriate cortex (V2), and beyond. Understanding the functional roles of these visual processing layers will not only help to understand psychophysical and neuroanatomical observations of these layers, but also would help to build intelligent computer vision systems that exhibit human-like behaviors and performance. One of the popular theories about the functional role of visual perception, the efficient coding theory, hypothesizes that the early visual processing layers serve to capture the statistical structure of the visual inputs by removing the redundancy in the visual outputs. Linear implementations of the efficient coding theory, such as independent component analysis (ICA) and sparse coding, learn visual features exhibiting the receptive field properties of V1 simple cells when they are applied to grayscale image patches. In this dissertation, we explore different aspects of the early visual processing layers by building computational models following the efficient coding theory. 1) We develop a hierarchical model, Recursive ICA, that captures nonlinear statistical structures of the visual inputs that cannot be captured by a single layer of ICA. The model is motivated by the idea that higher layers of the visual pathway, such as V2, might work under similar computational principles as the primary visual cortex. Hence we apply a second layer of ICA on top of the first layer ICA outputs. To allow the second layer of ICA to better capture nonlinear statistical structures, we derive a coordinate-wise nonlinear activation function that transforms the first layer ICA's outputs to the second layer ICA's inputs. When applied to grayscale image patches, the model's second layer learns nonlinear visual features, such as texture boundaries and shape contours. We apply the above model to natural scene images, such as forest and grassland, to learn some generic visual features, and then use these features for face and handwritten digit recognition. We get higher recognition rates than those systems built with features designed for face and digit recognition. (2) We show that retinal coding, the pre-cortical stage of visual processing, can also be explained by the efficient coding theory. The retinal coding model turns out to be another variation of Sparse PCA, a technique widely applied in signal processing, financial analysis, bioinformatics, etc. Compared with ICA, which removes the redundancy among the input dimensions, Sparse PCA removes redundancy among the input samples. We apply Sparse PCA to grayscale images, chromatic images, grayscale videos, environmental sound, and human speech, and learn visual and auditory features that exhibit the filtering properties of retinal ganglion cells and auditory nerve fibers. This work suggests that the pre-cortical stages of visual and auditory pathway might work under similar computational principles.

Download or read book Computational Models of Visual Processing written by Michael S. Landy and published by MIT Press. This book was released on 1991 with total page 420 pages. Available in PDF, EPUB and Kindle. Book excerpt: The more than twenty contributions in this book, all new and previously unpublished, provide an up-to-date survey of contemporary research on computational modeling of the visual system. The approaches represented range from neurophysiology to psychophysics, and from retinal function to the analysis of visual cues to motion, color, texture, and depth. The contributions are linked thematically by a consistent consideration of the links between empirical data and computational models in the study of visual function. An introductory chapter by Edward Adelson and James Bergen gives a new and elegant formalization of the elements of early vision. Subsequent sections treat receptors and sampling, models of neural function, detection and discrimination, color and shading, motion and texture, and 3D shape. Each section is introduced by a brief topical review and summary. ContributorsEdward H. Adelson, Albert J. Ahumada, Jr., James R. Bergen, David G. Birch, David H. Brainard, Heinrich H. Bülthoff, Charles Chubb, Nancy J. Coletta, Michael D'Zmura, John P. Frisby, Norma Graham, Norberto M. Grzywacz, P. William Haake, Michael J. Hawken, David J. Heeger, Donald C. Hood, Elizabeth B. Johnston, Daniel Kersten, Michael S. Landy, Peter Lennie, J. Stephen Mansfield, J. Anthony Movshon, Jacob Nachmias, Andrew J. Parker, Denis G. Pelli, Stephen B. Pollard, R. Clay Reid, Robert Shapley, Carlo L. M. Tiana, Brian A. Wandell, Andrew B. Watson, David R. Williams, Hugh R. Wilson, Yuede. Yang, Alan L. Yuille

Download or read book Models of Neural Networks IV written by J. Leo van Hemmen and published by Springer Science & Business Media. This book was released on 2012-11-09 with total page 424 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume, with chapters by leading researchers in the field, is devoted to early vision and attention, that is, to the first stages of visual information processing. This state-of-the-art look at biological neural networks spans the many subfields, such as computational and experimental neuroscience; anatomy and physiology; visual information processing and scene segmentation; perception at illusory contours; control of visual attention; and paradigms for computing with spiking neurons.

Download or read book Simple Cell Adaptation in Visual Cortex written by Alistair J. Bray and published by . This book was released on 1996 with total page 84 pages. Available in PDF, EPUB and Kindle. Book excerpt: Abstract: "This document describes an activity-based model of information processing in the early mammalian visual pathway. The work has been published previously in an abbreviated form [9], so this report is intended to present a more complete story. The model describes the retina, lateral geniculate nucleus (LGN), and development of simple cells in visual cortex (layer IVc of V1). In the retina we employ a non-adaptive model of on-centre and off-centre retinal ganglion cells (the tonic cells only) that is a non-linear approximation to difference-of-Gaussian processing. The output of this provides input to the LGN where the On and Off channels are kept separate. Here we simulate the effects of local inhibitory lateral interactions; this stage is also non-adaptive. Simple cells in the cortical model receive feedforward excitation from both the On and Off channels projecting out of the LGN. We propose a dual population model in which one population excites close neighbours while the other inhibits all neighbours within a greater area. We simulate this dynamic feedback using an iterative method, and when the network activity is stable we adapt all feedforward weights connecting simple cells to the LGN using a Hebbian (correlation-based) learning rule. We find that when presenting the network with many samples from natural images, the simple cells' feedforward weights adapt to become 'edge' and 'bar' detectors with receptive fields extremely similar to Gabor functions. These edge and bar detectors are orientation selective, and the orientation preference of different simple cells varies smoothly across the cortical surface. When plotting preferred orientation we get 'orientation maps' qualitatively similar to those documented in neurophysiological literature (in terms of smoothness & singularities). We examine these maps (and others) in terms of their auto-correlation matrix and orientation distribution. Finally we describe preliminary experiments in which the lateral connections within the cortex are adaptive; we find that regions of simple cells develop within which the cells have similar receptive fields but between which the cells have different receptive fields."

Download or read book Integrating Visual System Mechanisms Computational Models and Algorithms Technologies written by Hedva Spitzer and published by Frontiers Media SA. This book was released on 2020-05-26 with total page 233 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Models of Synaptic Development in Early Visual Cortex written by Harry G. Barrow and published by . This book was released on 1996 with total page 32 pages. Available in PDF, EPUB and Kindle. Book excerpt: Abstract: "This report is comprised of three independent parts describing developmental models for orientation selectivity, 'colour-blobs' and position-invariant complex cells respectively. Each of these models has been documented, in abbreviated form, in previously published work [1,2,3]. As such, these reports are intended to present 'the full story'. Part I describes an activity-based model of processing in the early visual pathway including retina, lateral geniculate nucleus (LGN), and simple cells in the cortex. We use a non-adaptive model of on- and off-centre retinal ganglion cells which project to the LGN. Cortical simple cells receive excitatory projections from the LGN. There are two populations of cortical cells: one population excites close neighbours whilst the other inhibits all neighbours within a greater area. When presented with input the network activity settles, after which feedforward weights connecting the simple and geniculate cells adapt using a Hebbian rule. After many presentations from natural images the feedforward weights adapt to become 'edge' and 'bar' detectors, with many receptive fields being similar to Gabor functions. These are orientation selective, and orientation preference varies smoothly across the cortical surface. Part II describes a model of colour-processing in the parvicellular visual pathway of primates. Principal component analysis of many small spatial samples taken from a natural colour image shows that only one of the eigenvectors with a large eigenvalue is significantly colour selective, and this eigenvector is not selective for 2D orientation. This result suggests an activity- based explanation for the formation of 'colour-blobs' in layer IVb of primate striate cortex. The work describes a network simulation of processing in the primate retina, LGN and V1 which self-organises in response to natural colour images and produces 'feature-maps' in which islands of a few colour-sensitive cells (i.e. colour blobs) are surrounded by a sea of oriented non-colour-selective cells. Part III proposes that complex cells in layers II & III of primate visual cortex learn to be sensitive to orientation, but invariant to position, through a mechanism similar to classical conditioning. A simulation is described with a simple computational model which demonstrates how complex cells can develop strong connections to simple cells with similar orientation preferences at different spatial positions by using a temporal version of the Hebbian learning rule. A further simulation with a detailed biological model of the primate visual pathway from retina to cortex supports the claim that complex cells learn orientation-selectivity but spatial invariance using temporal Hebbian learning."

Download or read book Encyclopedia of Computational Neuroscience written by Dieter Jaeger and published by . This book was released on with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Neural Computational Models of Superior Colliculus for Visual Processing written by Xiaoxing Wang and published by . This book was released on 2003 with total page 430 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book The Cambridge Handbook of Computational Psychology written by Ron Sun and published by Cambridge University Press. This book was released on 2008-04-28 with total page 767 pages. Available in PDF, EPUB and Kindle. Book excerpt: A cutting-edge reference source for the interdisciplinary field of computational cognitive modeling.

Download or read book Brain Inspired Computing written by Katrin Amunts and published by Springer Nature. This book was released on 2021-07-20 with total page 159 pages. Available in PDF, EPUB and Kindle. Book excerpt: This open access book constitutes revised selected papers from the 4th International Workshop on Brain-Inspired Computing, BrainComp 2019, held in Cetraro, Italy, in July 2019. The 11 papers presented in this volume were carefully reviewed and selected for inclusion in this book. They deal with research on brain atlasing, multi-scale models and simulation, HPC and data infra-structures for neuroscience as well as artificial and natural neural architectures.

Download or read book Integrating Computational and Neural Findings in Visual Object Perception written by Judith C. Peters and published by Frontiers Media SA. This book was released on 2016-06-29 with total page 139 pages. Available in PDF, EPUB and Kindle. Book excerpt: The articles in this Research Topic provide a state-of-the-art overview of the current progress in integrating computational and empirical research on visual object recognition. Developments in this exciting multidisciplinary field have recently gained momentum: High performance computing enabled breakthroughs in computer vision and computational neuroscience. In parallel, innovative machine learning applications have recently become available for datamining the large-scale, high resolution brain data acquired with (ultra-high field) fMRI and dense multi-unit recordings. Finally, new techniques to integrate such rich simulated and empirical datasets for direct model testing could aid the development of a comprehensive brain model. We hope that this Research Topic contributes to these encouraging advances and inspires future research avenues in computational and empirical neuroscience.

Download or read book Computational Cognitive Neuroscience written by Yuko Munakata and published by Independently Published. This book was released on 2012-09 with total page 188 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introduction to computer modeling of the brain, to understand how people think. Networks of interacting neurons produce complex emergent behavior including perception, attention, motor control, learning, memory, language, and executive functions (motivation, decision making, planning, etc).

Download or read book Models of the Visual System written by George K. Hung and published by Springer Science & Business Media. This book was released on 2013-11-11 with total page 777 pages. Available in PDF, EPUB and Kindle. Book excerpt: Some of the best vision scientists in the world in their respective fields have contributed to chapters in this book. They have expertise in a wide variety of fields, including bioengineering, basic and clinical visual science, medicine, neurophysiology, optometry, and psychology. Their combined efforts have resulted in a high quality book that covers modeling and quantitative analysis of optical, neurosensory, oculomotor, perceptual and clinical systems. It includes only those techniques and models that have such fundamentally strong physiological, control system, and perceptual bases that they will serve as foundations for models and analysis techniques in the future. The book is aimed first towards seniors and beginning graduate students in biomedical engineering, neurophysiology, optometry, and psychology, who will gain a broad understanding of quantitative analysis of the visual system. In addition, it has sufficient depth in each area to be useful as an updated reference and tutorial for graduate and post-doctoral students, as well as general vision scientists.

Download or read book Advances in the Modularity of Vision written by and published by National Academies. This book was released on 1990 with total page 74 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book The Role of Visual Processing in Computational Models of Reading written by Ya-Ning Chang and published by . This book was released on 2012 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Visual Selective Attention written by Claus Bundesen and published by Taylor & Francis. This book was released on 1995 with total page 300 pages. Available in PDF, EPUB and Kindle. Book excerpt: This special issue of Visual Cognition features empirical and theoretical contributions by leading research scholars in the field. The volume begins with a general introduction and an authoritative review of work on spatial attention in the flankers task. Next, a series of empirical articles reports important new findings on visual selection by spatial location. A second section contrasts by presenting recent empirical findings on visual selection by other criteria. Finally, four articles present major theoretical statements on aspects of visual attention. As a whole, the issue forms a substantial contribution to the literature on visual selective attention.

Download or read book Biological and Computer Vision written by Gabriel Kreiman and published by Cambridge University Press. This book was released on 2021-02-04 with total page 275 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book introduces neural mechanisms of biological vision and how artificial intelligence algorithms learn to interpret images.