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Mission-Oriented Sensor Networks and Systems: Art and Science = Volume 2: Advances /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Mission-Oriented Sensor Networks and Systems: Art and Science/ edited by Habib M. Ammari.
其他題名:	Volume 2: Advances /
其他作者:	Ammari, Habib M.
面頁冊數:	XVIII, 794 p. 303 illus., 188 illus. in color.online resource. :
Contained By:	Springer Nature eBook
標題:	Electrical engineering. -
電子資源:	https://doi.org/10.1007/978-3-319-92384-0
ISBN:	9783319923840

Mission-Oriented Sensor Networks and Systems: Art and Science = Volume 2: Advances /
Mission-Oriented Sensor Networks and Systems: Art and ScienceVolume 2: Advances /[electronic resource] :edited by Habib M. Ammari. - 1st ed. 2019. - XVIII, 794 p. 303 illus., 188 illus. in color.online resource. - Studies in Systems, Decision and Control,1642198-4182 ;. - Studies in Systems, Decision and Control,27.

Introduction -- Autonomous Cooperative Routing for Mission-Critical Applications -- Using Models for Communication in Cyber-Physical Systems -- Urban Micro-Climate Monitoring Using IoT Based Architecture -- Digital Forensics for IoT and WSNs -- An Overview of Wearable Computing -- Wearable Computing and Human Centricity -- Wireless transfer of energy alongside information in wireless sensor networks -- Efficient Protocols for Peer-to-Peer Wireless Power Transfer and Energy Aware Network Formation -- DeepCharge: Next-generation Software-defined Wireless Charging Systems -- Robotic Wireless Sensor Networks -- Robot and Drone Localization in GPS-Denied Areas -- Middleware for Multi-Robot System -- Interference Mitigation Techniques in Wireless Body Area Networks -- Radiation Control Algorithms in Wireless Networks -- Subspace based Encryption.

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.

ISBN: 9783319923840

Standard No.: 10.1007/978-3-319-92384-0doiSubjects--Topical Terms:

596380
Electrical engineering.

LC Class. No.: TK1-9971

Dewey Class. No.: 621.382

Mission-Oriented Sensor Networks and Systems: Art and Science = Volume 2: Advances /
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