Isbn: 9781032588674 - deep learning in internet of things for next generation healthcare (11 resultados)

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Librería: GreatBookPrices, Columbia, MD, Estados Unidos de AmericaGreatBookPrices
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Librería: California Books, Miami, FL, Estados Unidos de AmericaCalifornia Books
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Librería: GreatBookPricesUK, Woodford Green, Reino UnidoGreatBookPricesUK
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Librería: GreatBookPricesUK, Woodford Green, Reino UnidoGreatBookPricesUK
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Librería: Revaluation Books, Exeter, Reino UnidoRevaluation Books
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Paperback. Condición: Brand New. 288 pages. 7.00x0.65x10.00 inches. In Stock.

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Librería: moluna, Greven, Alemaniamoluna
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Condición: New. Dr. Lavanya Sharma is an assistant professor, Amity Institute of Information Technology at Amity University UP, Noida, India. She did her M.Tech (Computer Science and Engineering) in 2013 at Manav Rachna College of Engineering, affiliated with Mah.

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Librería: AHA-BUCH GmbH, Einbeck, AlemaniaAHA-BUCH GmbH
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EUR 109,30
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Taschenbuch. Condición: Neu. Neuware - This book presents the latest developments in deep learning-enabled healthcare tools and technologies and offers practical ideas for using the IoT with deep learning (motion-based object data) to deal with human dynamics and challenges including critical application domains, technologies, medical imaging, drug discovery, insurance fraud detection and solutions to handle relevant challenges. This book covers real-time healthcare applications, novel solutions, current open challenges, and the future of deep learning for next-generation healthcare. It includes detailed analysis of the utilization of the IoT with deep learning and its underlying technologies in critical application areas of emergency departments such as drug discovery, medical imaging, fraud detection, Alzheimer's disease, and genomes. - Presents practical approaches of using the IoT with deep learning vision and how it deals with human dynamics - Offers novel solution for medical imaging including skin lesion detection, cancer detection, enhancement techniques for MRI images, automated disease prediction, fraud detection, genomes, and many more - Includes the latest technological advances in the IoT and deep learning with their implementations in healthcare - Combines deep learning and analysis in the unified framework to understand both IoT and deep learning applications - Covers the challenging issues related to data collection by sensors, detection and tracking of moving objects and solutions to handle relevant challenges Postgraduate students and researchers in the departments of computer science, working in the areas of the IoT, deep learning, machine learning, image processing, big data, cloud computing, and remote sensing will find this book useful.…

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Librería: AussieBookSeller, Truganina, VIC, AustraliaAussieBookSeller
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Paperback. Condición: new. Paperback. This book presents the latest developments in deep learning-enabled healthcare tools and technologies and offers practical ideas for using the IoT with deep learning (motion-based object data) to deal with human dynamics and challenges including critical application domains, technologies, medical imaging, drug discovery, insurance fraud detection and solutions to handle relevant challenges. This book covers real-time healthcare applications, novel solutions, current open challenges, and the future of deep learning for next-generation healthcare. It includes detailed analysis of the utilization of the IoT with deep learning and its underlying technologies in critical application areas of emergency departments such as drug discovery, medical imaging, fraud detection, Alzheimer's disease, and genomes.Presents practical approaches of using the IoT with deep learning vision and how it deals with human dynamicsOffers novel solution for medical imaging including skin lesion detection, cancer detection, enhancement techniques for MRI images, automated disease prediction, fraud detection, genomes, and many moreIncludes the latest technological advances in the IoT and deep learning with their implementations in healthcareCombines deep learning and analysis in the unified framework to understand both IoT and deep learning applicationsCovers the challenging issues related to data collection by sensors, detection and tracking of moving objects and solutions to handle relevant challengesPostgraduate students and researchers in the departments of computer science, working in the areas of the IoT, deep learning, machine learning, image processing, big data, cloud computing, and remote sensing will find this book useful. This book presents latest developments in deep learning-enabled healthcare tools and technologies and offers practical ideas of using IoT with deep learning (motion-based object data) to deal with human dynamics, and challenges. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.…