000 | 03796nam a22005415i 4500 | ||
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001 | 978-3-319-92384-0 | ||
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007 | cr nn 008mamaa | ||
008 | 190918s2019 sz | s |||| 0|eng d | ||
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_a9783319923840 _9978-3-319-92384-0 |
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_a10.1007/978-3-319-92384-0 _2doi |
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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. |
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300 |
_aXVIII, 794 p. 303 illus., 188 illus. in color. _bonline resource. |
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336 |
_atext _btxt _2rdacontent |
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337 |
_acomputer _bc _2rdamedia |
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_aonline resource _bcr _2rdacarrier |
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347 |
_atext file _bPDF _2rda |
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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 |
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650 | 0 |
_aControl engineering. _931970 |
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650 | 0 |
_aRobotics. _92393 |
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650 | 0 |
_aAutomation. _92392 |
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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 |
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710 | 2 |
_aSpringerLink (Online service) _940918 |
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773 | 0 | _tSpringer Nature eBook | |
776 | 0 | 8 |
_iPrinted edition: _z9783319923833 |
776 | 0 | 8 |
_iPrinted edition: _z9783319923857 |
830 | 0 |
_aStudies in Systems, Decision and Control, _x2198-4190 ; _v164 _940919 |
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856 | 4 | 0 | _uhttps://doi.org/10.1007/978-3-319-92384-0 |
912 | _aZDB-2-ENG | ||
912 | _aZDB-2-SXE | ||
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