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Titlebook: Mission-Oriented Sensor Networks and Systems: Art and Science; Volume 2: Advances Habib M. Ammari Book 2019 Springer Nature Switzerland AG

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書目名稱Mission-Oriented Sensor Networks and Systems: Art and Science
副標(biāo)題Volume 2: Advances
編輯Habib M. Ammari
視頻videohttp://file.papertrans.cn/635/634797/634797.mp4
概述Provides a concise and structured presentation of deep learning applications.Introduces a large range of applications related to vision, speech, and natural language processing.Includes active researc
叢書名稱Studies in Systems, Decision and Control
圖書封面Titlebook: Mission-Oriented Sensor Networks and Systems: Art and Science; Volume 2: Advances Habib M. Ammari Book 2019 Springer Nature Switzerland AG
描述.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..
出版日期Book 2019
關(guān)鍵詞Mission-Oriented Wireless Sensor Networks; WSN; Sensors; Networks; Sensor-based Application Design
版次1
doihttps://doi.org/10.1007/978-3-319-92384-0
isbn_ebook978-3-319-92384-0Series ISSN 2198-4182 Series E-ISSN 2198-4190
issn_series 2198-4182
copyrightSpringer Nature Switzerland AG 2019
The information of publication is updating

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2198-4182 e 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..978-3-319-92384-0Series ISSN 2198-4182 Series E-ISSN 2198-4190
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Habib M. AmmariProvides a concise and structured presentation of deep learning applications.Introduces a large range of applications related to vision, speech, and natural language processing.Includes active researc
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Mission-Oriented Sensor Networks and Systems: Art and Science978-3-319-92384-0Series ISSN 2198-4182 Series E-ISSN 2198-4190
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