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Mission-Oriented Sensor Networks and Systems: Art and Science - Volume 2: Advances (Hardcover, 1st ed. 2019) Loot Price: R5,609
Discovery Miles 56 090
Mission-Oriented Sensor Networks and Systems: Art and Science - Volume 2: Advances (Hardcover, 1st ed. 2019): Habib M. Ammari

Mission-Oriented Sensor Networks and Systems: Art and Science - Volume 2: Advances (Hardcover, 1st ed. 2019)

Habib M. Ammari

Series: Studies in Systems, Decision and Control, 164

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Loot Price R5,609 Discovery Miles 56 090 | Repayment Terms: R526 pm x 12*

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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.

General

Imprint: Springer International Publishing AG
Country of origin: Switzerland
Series: Studies in Systems, Decision and Control, 164
Release date: October 2019
First published: 2019
Editors: Habib M. Ammari
Dimensions: 235 x 155mm (L x W)
Format: Hardcover
Pages: 794
Edition: 1st ed. 2019
ISBN-13: 978-3-319-92383-3
Categories: Books > Professional & Technical > Electronics & communications engineering > Communications engineering / telecommunications > General
Books > Professional & Technical > Electronics & communications engineering > Electronics engineering > Automatic control engineering > General
LSN: 3-319-92383-8
Barcode: 9783319923833

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