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020 _a9783319923840
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024 7 _a10.1007/978-3-319-92384-0
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_2bicssc
072 7 _aTEC041000
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072 7 _aTJK
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082 0 4 _a621.382
_223
245 1 0 _aMission-Oriented Sensor Networks and Systems: Art and Science
_h[electronic resource] :
_bVolume 2: Advances /
_cedited by Habib M. Ammari.
250 _a1st ed. 2019.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2019.
300 _aXVIII, 794 p. 303 illus., 188 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
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490 1 _aStudies in Systems, Decision and Control,
_x2198-4190 ;
_v164
505 0 _aIntroduction -- 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.
520 _aThis 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.
650 0 _aTelecommunication.
_910437
650 0 _aControl engineering.
_931970
650 0 _aRobotics.
_92393
650 0 _aAutomation.
_92392
650 1 4 _aCommunications Engineering, Networks.
_931570
650 2 4 _aControl, Robotics, Automation.
_931971
650 2 4 _aControl and Systems Theory.
_931972
700 1 _aAmmari, Habib M.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_940917
710 2 _aSpringerLink (Online service)
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773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783319923833
776 0 8 _iPrinted edition:
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830 0 _aStudies in Systems, Decision and Control,
_x2198-4190 ;
_v164
_940919
856 4 0 _uhttps://doi.org/10.1007/978-3-319-92384-0
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