Visual Cortex And Deep Networks

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Visual Cortex and Deep Networks

Author : Tomaso A. Poggio
Publisher : MIT Press
ISBN 13 : 0262336723
Total Pages : 135 pages
Book Rating : 4.2/5 (623 download)

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Book Synopsis Visual Cortex and Deep Networks by : Tomaso A. Poggio

Download or read book Visual Cortex and Deep Networks written by Tomaso A. Poggio and published by MIT Press. This book was released on 2016-09-23 with total page 135 pages. Available in PDF, EPUB and Kindle. Book excerpt: A mathematical framework that describes learning of invariant representations in the ventral stream, offering both theoretical development and applications. The ventral visual stream is believed to underlie object recognition in primates. Over the past fifty years, researchers have developed a series of quantitative models that are increasingly faithful to the biological architecture. Recently, deep learning convolution networks—which do not reflect several important features of the ventral stream architecture and physiology—have been trained with extremely large datasets, resulting in model neurons that mimic object recognition but do not explain the nature of the computations carried out in the ventral stream. This book develops a mathematical framework that describes learning of invariant representations of the ventral stream and is particularly relevant to deep convolutional learning networks. The authors propose a theory based on the hypothesis that the main computational goal of the ventral stream is to compute neural representations of images that are invariant to transformations commonly encountered in the visual environment and are learned from unsupervised experience. They describe a general theoretical framework of a computational theory of invariance (with details and proofs offered in appendixes) and then review the application of the theory to the feedforward path of the ventral stream in the primate visual cortex.

Visual Cortex and Deep Networks

Author : Tomaso A. Poggio
Publisher : MIT Press
ISBN 13 : 0262034727
Total Pages : 135 pages
Book Rating : 4.2/5 (62 download)

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Book Synopsis Visual Cortex and Deep Networks by : Tomaso A. Poggio

Models of Neural Networks IV

Author : J. Leo van Hemmen
Publisher : Springer Science & Business Media
ISBN 13 : 9780387951058
Total Pages : 438 pages
Book Rating : 4.9/5 (51 download)

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Book Synopsis Models of Neural Networks IV by : J. Leo van Hemmen

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 2002 with total page 438 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.

Convolutional Neural Networks

Author : Fouad Sabry
Publisher : One Billion Knowledgeable
ISBN 13 :
Total Pages : 169 pages
Book Rating : 4.:/5 (661 download)

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Book Synopsis Convolutional Neural Networks by : Fouad Sabry

Download or read book Convolutional Neural Networks written by Fouad Sabry and published by One Billion Knowledgeable. This book was released on 2023-06-26 with total page 169 pages. Available in PDF, EPUB and Kindle. Book excerpt: What Is Convolutional Neural Networks In the field of deep learning, a convolutional neural network, also known as a CNN, is a type of artificial neural network that is typically used to conduct analysis on visual data. At least one of the layers in a CNN substitutes the mathematical operation of convolution, sometimes known as convolving, for the more traditional matrix multiplication. They are utilized in both the image recognition and processing processes, as their primary purpose is the processing of pixel data. Applications can be found in areas such as image and video recognition, recommender systems, and more.image classification,image segmentation,image analysis for medical purposes,natural language processing,interfaces between the human brain and computers, andfinance time series. How You Will Benefit (I) Insights, and validations about the following topics: Chapter 1: Convolutional Neural Network Chapter 2: Artificial Neural Network Chapter 3: Types of Artificial Neural Networks Chapter 4: Deep Learning Chapter 5: Activation Function Chapter 6: Layer (Deep Learning) Chapter 7: LeNet Chapter 8: Tensor (Machine Learning) Chapter 9: Receptive Field Chapter 10: History of Artificial Neural Networks (II) Answering the public top questions about convolutional neural networks. (III) Real world examples for the usage of convolutional neural networks in many fields. Who This Book Is For Professionals, undergraduate and graduate students, enthusiasts, hobbyists, and those who want to go beyond basic knowledge or information for any kind of convolutional neural networks. What Is Artificial Intelligence Series The Artificial Intelligence eBook series provides comprehensive coverage in over 200 topics. Each ebook covers a specific Artificial Intelligence topic in depth, written by experts in the field. The series aims to give readers a thorough understanding of the concepts, techniques, history and applications of artificial intelligence. Topics covered include machine learning, deep learning, neural networks, computer vision, natural language processing, robotics, ethics and more. The ebooks are written for professionals, students, and anyone interested in learning about the latest developments in this rapidly advancing field. The Artificial Intelligence eBook series provides an in-depth yet accessible exploration, from the fundamental concepts to the state-of-the-art research. With over 200 volumes, readers gain a thorough grounding in all aspects of Artificial Intelligence. The ebooks are designed to build knowledge systematically, with later volumes building on the foundations laid by earlier ones. This comprehensive series is an indispensable resource for anyone seeking to develop expertise in artificial intelligence.

Unveiling Functions of the Visual Cortex Using Task-specific Deep Neural Networks

Author : Kshitij Dwivedi
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (137 download)

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Book Synopsis Unveiling Functions of the Visual Cortex Using Task-specific Deep Neural Networks by : Kshitij Dwivedi

Download or read book Unveiling Functions of the Visual Cortex Using Task-specific Deep Neural Networks written by Kshitij Dwivedi and published by . This book was released on 2021 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Vision

Author : Jeanny Hrault
Publisher : World Scientific
ISBN 13 : 9814273694
Total Pages : 308 pages
Book Rating : 4.8/5 (142 download)

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Book Synopsis Vision by : Jeanny Hrault

Download or read book Vision written by Jeanny Hrault and published by World Scientific. This book was released on 2010 with total page 308 pages. Available in PDF, EPUB and Kindle. Book excerpt: At the fascinating frontiers of neurobiology, mathematics and psychophysics, this book addresses the problem of human and computer vision on the basis of cognitive modeling. After recalling the physics of light and its transformation through media and optics, Hrault presents the principles of the primate's visual system in terms of anatomy and functionality. Then, the neuronal circuitry of the retina is analyzed in terms of spatio?temporal filtering. This basic model is extended to the concept of neuromorphic circuits for motion processing and to the processing of color in the retina. For more in-depth studies, the adaptive non-linear properties of the photoreceptors and of ganglion cells are addressed, exhibiting all the power of the retinal pre-processing of images as a system of information cleaning suitable for further cortical processing. As a target of retinal information, the primary visual area is presented as a bank of filters able to extract valuable descriptors of images, suitable for categorization and recognition and also for local information extraction such as saliency and perspective. All along the book, many comparisons between the models and human perception are discussed as well as detailed applications to computer vision.

Data-Driven Science and Engineering

Author : Steven L. Brunton
Publisher : Cambridge University Press
ISBN 13 : 1009098489
Total Pages : 615 pages
Book Rating : 4.0/5 (9 download)

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Book Synopsis Data-Driven Science and Engineering by : Steven L. Brunton

Download or read book Data-Driven Science and Engineering written by Steven L. Brunton and published by Cambridge University Press. This book was released on 2022-05-05 with total page 615 pages. Available in PDF, EPUB and Kindle. Book excerpt: A textbook covering data-science and machine learning methods for modelling and control in engineering and science, with Python and MATLAB®.

Computational Maps in the Visual Cortex

Author : Risto Miikkulainen
Publisher : Springer Science & Business Media
ISBN 13 : 0387288066
Total Pages : 547 pages
Book Rating : 4.3/5 (872 download)

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Book Synopsis Computational Maps in the Visual Cortex by : Risto Miikkulainen

Download or read book Computational Maps in the Visual Cortex written by Risto Miikkulainen and published by Springer Science & Business Media. This book was released on 2006-01-16 with total page 547 pages. Available in PDF, EPUB and Kindle. Book excerpt: For more than 30 years, the visual cortex has been the source of new theories and ideas about how the brain processes information. The visual cortex is easily accessible through a variety of recording and imagining techniques and allows mapping of high level behavior relatively directly to neural mechanisms. Understanding the computations in the visual cortex is therefore an important step toward a general theory of computational brain theory.

Biological and Computer Vision

Author : Gabriel Kreiman
Publisher : Cambridge University Press
ISBN 13 : 1108759262
Total Pages : 275 pages
Book Rating : 4.1/5 (87 download)

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Book Synopsis Biological and Computer Vision by : Gabriel Kreiman

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: Imagine a world where machines can see and understand the world the way humans do. Rapid progress in artificial intelligence has led to smartphones that recognize faces, cars that detect pedestrians, and algorithms that suggest diagnoses from clinical images, among many other applications. The success of computer vision is founded on a deep understanding of the neural circuits in the brain responsible for visual processing. This book introduces the neuroscientific study of neuronal computations in visual cortex alongside of the psychological understanding of visual cognition and the burgeoning field of biologically-inspired artificial intelligence. Topics include the neurophysiological investigation of visual cortex, visual illusions, visual disorders, deep convolutional neural networks, machine learning, and generative adversarial networks among others. It is an ideal resource for students and researchers looking to build bridges across different approaches to studying and developing visual systems.

A Neural Network Model of the Primary Visual Cortex

Author : Alan Spara
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (124 download)

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Book Synopsis A Neural Network Model of the Primary Visual Cortex by : Alan Spara

Download or read book A Neural Network Model of the Primary Visual Cortex written by Alan Spara and published by . This book was released on 2008 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Many problems in modern computing require a visual component. That is to say, it is fairly common for applications to have a need to see their environments. These applications will typically employ techniques designed specifically to solve the particular task needed for the application, and have little or no relation to the human visual system. Humans generally do not have difficulty interpreting the world around us. When traveling through known environments, we can easily recognize particular walls, doors and other objects in our view. We are not confused by the huge number factors that can complicate an image. The generalization and robustness of the human system would provide a huge benefit to any system that requires more advanced vision than is capable with the ad-hoc methods developed previously. If the underlying principles that make the human visual system so powerful can be identified and implemented programmatically, then a machine could reap the benefits obtained by humans. The purpose of this thesis is to demonstrate that a visual system modeled after the human visual system will be robust and accurate enough to solve real world problems - and to be useful in a non-trivial application. By developing neural networks that directly model the most primitive image processing cells of the human visual system, a platform can be built on which advanced vision systems can be developed.

Cognitive and Neural Modelling for Visual Information Representation and Memorization

Author : Limiao Deng
Publisher : CRC Press
ISBN 13 : 1000574652
Total Pages : 183 pages
Book Rating : 4.0/5 (5 download)

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Book Synopsis Cognitive and Neural Modelling for Visual Information Representation and Memorization by : Limiao Deng

Download or read book Cognitive and Neural Modelling for Visual Information Representation and Memorization written by Limiao Deng and published by CRC Press. This book was released on 2022-04-24 with total page 183 pages. Available in PDF, EPUB and Kindle. Book excerpt: Focusing on how visual information is represented, stored and extracted in the human brain, this book uses cognitive neural modeling in order to show how visual information is represented and memorized in the brain. Breaking through traditional visual information processing methods, the author combines our understanding of perception and memory from the human brain with computer vision technology, and provides a new approach for image recognition and classification. While biological visual cognition models and human brain memory models are established, applications such as pest recognition and carrot detection are also involved in this book. Given the range of topics covered, this book is a valuable resource for students, researchers and practitioners interested in the rapidly evolving field of neurocomputing, computer vision and machine learning.

A self-organizing neural network model of the primary visual cortex

Author : Joseph Sirosh
Publisher :
ISBN 13 :
Total Pages : 398 pages
Book Rating : 4.:/5 (359 download)

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Book Synopsis A self-organizing neural network model of the primary visual cortex by : Joseph Sirosh

Download or read book A self-organizing neural network model of the primary visual cortex written by Joseph Sirosh and published by . This book was released on 1995 with total page 398 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Neural Network Modeling for Brain Visual Cortex

Author : Beeior Rov-Ikpah
Publisher :
ISBN 13 :
Total Pages : 100 pages
Book Rating : 4.:/5 (13 download)

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Book Synopsis Neural Network Modeling for Brain Visual Cortex by : Beeior Rov-Ikpah

Download or read book Neural Network Modeling for Brain Visual Cortex written by Beeior Rov-Ikpah and published by . This book was released on 2016 with total page 100 pages. Available in PDF, EPUB and Kindle. Book excerpt:

A Unified Model of the Structure and Function of Primate Visual Cortex

Author : Eshed Margalit
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (134 download)

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Book Synopsis A Unified Model of the Structure and Function of Primate Visual Cortex by : Eshed Margalit

Download or read book A Unified Model of the Structure and Function of Primate Visual Cortex written by Eshed Margalit and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Humans have the remarkable capacity to recognize visual objects despite challenging variations in their pose, illumination, and context. This ability depends on the ventral visual stream, a series of cortical areas that progressively transforms the signal from the retina into representations of object category, location, color, texture, and size. Our understanding of the function and development of the ventral visual stream is anchored in the tight coupling between structure and function in the constituent cortical areas: in each area, neurons are arranged in the cortical sheet according to the visual features they respond most strongly to. In the earliest stage of the ventral visual stream neighboring neurons preferentially respond to edges of similar orientations and colors, whereas neurons toward the end of the ventral stream cluster together according to their preferred object category, e.g., faces, limbs, and places. Understanding the development and purpose of this functional organization requires the construction of detailed models whose predictions can be evaluated against neural measurements. In this dissertation, I present topographic deep convolutional neural networks (topographic DCNNs) as unifying models of neural structure and function throughout the ventral visual stream. Topographic DCNNs implement the simple hypothesis that functional organization in the visual cortex can be reproduced by optimizing the parameters of a neural network to perform a challenging visual task while keeping local populations of neurons correlated with one another. I find that topographic DCNNs are able to reproduce functional organization in both early and later stages of the ventral visual stream, that this brain-model correspondence is strongest for more biologically-plausible learning algorithms, and that topographic DCNNs can be used to predict how changes to visual inputs during development will affect cortical map formation. The success of topographic DCNNs in the prediction of the functional organization of the primate ventral visual stream implies the existence of simple unifying principles for the development of those regions, and serves as a foundation from which increasingly accurate models of visual processing can be constructed.

An Introduction to Neural Networks

Author : James A. Anderson
Publisher : MIT Press
ISBN 13 : 9780262510813
Total Pages : 680 pages
Book Rating : 4.5/5 (18 download)

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Book Synopsis An Introduction to Neural Networks by : James A. Anderson

Download or read book An Introduction to Neural Networks written by James A. Anderson and published by MIT Press. This book was released on 1995 with total page 680 pages. Available in PDF, EPUB and Kindle. Book excerpt: An Introduction to Neural Networks falls into a new ecological niche for texts. Based on notes that have been class-tested for more than a decade, it is aimed at cognitive science and neuroscience students who need to understand brain function in terms of computational modeling, and at engineers who want to go beyond formal algorithms to applications and computing strategies. It is the only current text to approach networks from a broad neuroscience and cognitive science perspective, with an emphasis on the biology and psychology behind the assumptions of the models, as well as on what the models might be used for. It describes the mathematical and computational tools needed and provides an account of the author's own ideas. Students learn how to teach arithmetic to a neural network and get a short course on linear associative memory and adaptive maps. They are introduced to the author's brain-state-in-a-box (BSB) model and are provided with some of the neurobiological background necessary for a firm grasp of the general subject. The field now known as neural networks has split in recent years into two major groups, mirrored in the texts that are currently available: the engineers who are primarily interested in practical applications of the new adaptive, parallel computing technology, and the cognitive scientists and neuroscientists who are interested in scientific applications. As the gap between these two groups widens, Anderson notes that the academics have tended to drift off into irrelevant, often excessively abstract research while the engineers have lost contact with the source of ideas in the field. Neuroscience, he points out, provides a rich and valuable source of ideas about data representation and setting up the data representation is the major part of neural network programming. Both cognitive science and neuroscience give insights into how this can be done effectively: cognitive science suggests what to compute and neuroscience suggests how to compute it.

Time-Space, Spiking Neural Networks and Brain-Inspired Artificial Intelligence

Author : Nikola K. Kasabov
Publisher : Springer
ISBN 13 : 3662577151
Total Pages : 742 pages
Book Rating : 4.6/5 (625 download)

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Book Synopsis Time-Space, Spiking Neural Networks and Brain-Inspired Artificial Intelligence by : Nikola K. Kasabov

Download or read book Time-Space, Spiking Neural Networks and Brain-Inspired Artificial Intelligence written by Nikola K. Kasabov and published by Springer. This book was released on 2018-08-29 with total page 742 pages. Available in PDF, EPUB and Kindle. Book excerpt: Spiking neural networks (SNN) are biologically inspired computational models that represent and process information internally as trains of spikes. This monograph book presents the classical theory and applications of SNN, including original author’s contribution to the area. The book introduces for the first time not only deep learning and deep knowledge representation in the human brain and in brain-inspired SNN, but takes that further to develop new types of AI systems, called in the book brain-inspired AI (BI-AI). BI-AI systems are illustrated on: cognitive brain data, including EEG, fMRI and DTI; audio-visual data; brain-computer interfaces; personalized modelling in bio-neuroinformatics; multisensory streaming data modelling in finance, environment and ecology; data compression; neuromorphic hardware implementation. Future directions, such as the integration of multiple modalities, such as quantum-, molecular- and brain information processing, is presented in the last chapter. The book is a research book for postgraduate students, researchers and practitioners across wider areas, including computer and information sciences, engineering, applied mathematics, bio- and neurosciences.

Neural Networks for Vision and Image Processing

Author : Gail A. Carpenter
Publisher : Springer Science & Business
ISBN 13 : 9780262531085
Total Pages : 492 pages
Book Rating : 4.5/5 (31 download)

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Book Synopsis Neural Networks for Vision and Image Processing by : Gail A. Carpenter

Download or read book Neural Networks for Vision and Image Processing written by Gail A. Carpenter and published by Springer Science & Business. This book was released on 1992 with total page 492 pages. Available in PDF, EPUB and Kindle. Book excerpt: This interdisciplinary survey brings together recent models and experiments on how the brain sees and learns to recognize objects. It shows how to use these insights in technology and describes how neural networks provide a unifying computational framework for reaching these goals. Several chapters describe experiments in neurobiology and visual perception that clarify properties of biological vision and key conceptual issues that biological models need to address. Other chapters describe neural and computational models of biological vision that address such issues and clarify processes whereby biological vision derives its remarkable flexibility and power. Still other chapters use biologically derived models or heuristics to suggest neural network solutions to challenging technological problems in computer vision. Topics range from analyses of motion, depth, color and form to new concepts about learning, attention, pattern recognition, and hardware implementation.