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A Guide to Convolutional Neural Networks for Computer Vision, Salman Khan, Hossein Rahmani, Syed Afaq Ali Shah, Mohammed Bennamoun


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Автор: Salman Khan, Hossein Rahmani, Syed Afaq Ali Shah, Mohammed Bennamoun
Название:  A Guide to Convolutional Neural Networks for Computer Vision
ISBN: 9781681732787
Издательство: Mare Nostrum (Eurospan)
Классификация:



ISBN-10: 1681732785
Обложка/Формат: Hardcover
Страницы: 207
Вес: 0.58 кг.
Дата издания: 28.02.2018
Серия: Synthesis lectures on computer vision
Язык: English
Размер: 235 x 191 x 13
Ключевые слова: Artificial intelligence,Machine learning,Neural networks & fuzzy systems,Computer vision, COMPUTERS / Computer Vision & Pattern Recognition,COMPUTERS / Intelligence (AI) & Semantics,COMPUTERS / Neural Networks
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Поставляется из: Англии
Описание: Computer vision has become increasingly important and effective in recent years due to its wide-ranging applications in areas as diverse as smart surveillance and monitoring, health and medicine, sports and recreation, robotics, drones, and self-driving cars. Visual recognition tasks, such as image classification, localization, and detection, are the core building blocks of many of these applications, and recent developments in Convolutional Neural Networks (CNNs) have led to outstanding performance in these state-of-the-art visual recognition tasks and systems. As a result, CNNs now form the crux of deep learning algorithms in computer vision.This self-contained guide will benefit those who seek to both understand the theory behind CNNs and to gain hands-on experience on the application of CNNs in computer vision. It provides a comprehensive introduction to CNNs starting with the essential concepts behind neural networks: training, regularization, and optimization of CNNs. The book also discusses a wide range of loss functions, network layers, and popular CNN architectures, reviews the different techniques for the evaluation of CNNs, and presents some popular CNN tools and libraries that are commonly used in computer vision. Further, this text describes and discusses case studies that are related to the application of CNN in computer vision, including image classification, object detection, semantic segmentation, scene understanding, and image generation.This book is ideal for undergraduate and graduate students, as no prior background knowledge in the field is required to follow the material, as well as new researchers, developers, engineers, and practitioners who are interested in gaining a quick understanding of CNN models.

Convolutional Neural Networks In Vi

Автор: Venkatesan, Ragav,
Название: Convolutional Neural Networks In Vi
ISBN: 1498770398 ISBN-13(EAN): 9781498770392
Издательство: Taylor&Francis
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Цена: 168430.00 T
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Описание: This book covers the fundamentals in designing and deploying techniques using deep architectures. It is intended to serve as a beginner`s guide to engineers or students who want to have a quick start on learning and/or building deep learning systems.

Deep Learning for Computer Architects

Автор: Brandon Reagen, Robert Adolf, Paul Whatmough, Gu-Yeon Wei, David Brooks
Название: Deep Learning for Computer Architects
ISBN: 168173219X ISBN-13(EAN): 9781681732190
Издательство: Mare Nostrum (Eurospan)
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Цена: 76690.00 T
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Описание: A primer for computer architects in a new and rapidly evolving field. The authors review how machine learning has evolved since its inception in the 1960s and track the key developments leading up to the emergence of the powerful deep learning techniques that have emerged in the last decade.

Blind Equalization in Neural Networks

Автор: Zhang Tsinghua University Press Liyi
Название: Blind Equalization in Neural Networks
ISBN: 3110449625 ISBN-13(EAN): 9783110449624
Издательство: Walter de Gruyter
Цена: 123910.00 T
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Описание: The book begins with an introduction of blind equalization theory and its application in neural networks, then discusses the algorithms in recurrent networks, fuzzy networks and other frequently-studied neural networks. Each algorithm is accompanied by derivation, modeling and simulation, making the book an essential reference for electrical engineers, computer intelligence researchers and neural scientists.

Neural Networks, Fuzzy Systems and Evolutionary Algorithms: Synthesis and Applications

Автор: S. Rajasekaran, G.A. Vijayalakshmi Pai
Название: Neural Networks, Fuzzy Systems and Evolutionary Algorithms: Synthesis and Applications
ISBN: 812035334X ISBN-13(EAN): 9788120353343
Издательство: Mare Nostrum (Eurospan)
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Цена: 20330.00 T
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Описание: Provides a comprehensive introduction to a consortium of technologies underlying soft computing. The constituent technologies discussed comprise neural network (NN), fuzzy system (FS), evolutionary algorithm (EA), and a number of hybrid systems, which include classes such as neuro-fuzzy, evolutionary-fuzzy, and neuro-evolutionary systems.

Space-Time Computing with Temporal Neural Networks

Автор: James E. Smith
Название: Space-Time Computing with Temporal Neural Networks
ISBN: 1627059482 ISBN-13(EAN): 9781627059480
Издательство: Mare Nostrum (Eurospan)
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Цена: 82230.00 T
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Описание: Written from the perspective of a computer designer and targeted at computer researchers, this volume is intended to give both background and lay out a course of action for studying the brain`s computational paradigm. It contains a mix of concepts and ideas drawn from computational neuroscience, combined with those of the author.


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