Mission-Oriented Sensor Networks and Systems: Art and Science
Volume 2: Advances
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Beschreibung
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.
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.
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 research trends, challenges, and future directions of deep learning
Presents recent research in Mission-Oriented Wireless Sensor Networks
Written for practitioners and researchers from both industry and academia
Focuses on major challenges in the design of Mission-Oriented WSNs due to their dynamic topology and architecture, which are caused mainly by sensing devices mobility
Autor*in
Habib M. Ammari
Themen in »Mission-Oriented Sensor Networks and Systems: Art and Science«
Mission-Oriented Wireless Sensor Networks WSN Sensors Networks Sensor-based Application Design