Mission-Oriented Sensor Networks and Systems: Art and Science: Volume 2: Advances: 164 (Studies in Systems, Decision and Control, 164) - Hardcover

Book 213 of 378: Studies in Systems, Decision and Control
 
9783319923833: Mission-Oriented Sensor Networks and Systems: Art and Science: Volume 2: Advances: 164 (Studies in Systems, Decision and Control, 164)
Hardcover
ISBN 10: 3319923838 ISBN 13: 9783319923833
Publisher: Springer International Publishing AG, 2019

Synopsis

This book presents a broad range of deep-learning applications related to vision, natural language processing, gene expression, arbitrary object recognition, driverless cars, semantic image segmentation, deep visual residual abstraction, brain–computer interfaces, big data processing, hierarchical deep learning networks as game-playing artefacts using regret matching, and building GPU-accelerated deep learning frameworks. Deep learning, an advanced level of machine learning technique that combines class of learning algorithms with the use of many layers of nonlinear units, has gained considerable attention in recent times. Unlike other books on the market, this volume addresses the challenges of deep learning implementation, computation time, and the complexity of reasoning and modeling different type of data. As such, it is a valuable and comprehensive resource for engineers, researchers, graduate students and Ph.D. scholars.

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From the Back Cover

This book presents a broad range of deep-learning applications related to vision, natural language processing, gene expression, arbitrary object recognition, driverless cars, semantic image segmentation, deep visual residual abstraction, brain-computer interfaces, big data processing, hierarchical deep learning networks as game-playing artefacts using regret matching, and building GPU-accelerated deep learning frameworks. Deep learning, an advanced level of machine learning technique that combines class of learning algorithms with the use of many layers of nonlinear units, has gained considerable attention in recent times. Unlike other books on the market, this volume addresses the challenges of deep learning implementation, computation time, and the complexity of reasoning and modeling different type of data. As such, it is a valuable and comprehensive resource for engineers, researchers, graduate students and Ph.D. scholars.


"About this title" may belong to another edition of this title.

Publisher
Springer International Publishing AG
Publication date
2019
Language
English
ISBN 10 
3319923838
ISBN 13 
9783319923833
Binding
Hardcover
Number of pages
812
Editor
Ammari Habib M.