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"Deep learning algorithms have brought a revolution to the computer vision community by introducing non-traditional and efficient solutions to several image-related problems that had long remained unsolved or partially addressed. This book presents a collection of eleven chapters where each individual chapter explains the deep learning principles of a specific topic, introduces reviews of up-to-date techniques, and presents research findings to the computer vision community. The book covers a broad scope of topics in deep learning concepts and applications such as accelerating the convolutional neural network inference on field-programmable gate arrays, fire detection in surveillance applications, face recognition, action and activity recognition, semantic segmentation for autonomous driving, aerial imagery registration, robot vision, tumor detection, and skin lesion segmentation as well as skin melanoma classification. The content of this book has been organized such that each chapter can be read independently from the others. The book is a valuable companion for researchers, postgraduate and possibly senior undergraduate students who are taking an advanced course in related topics, and for those who are interested in deep learning with applications in computer vision, image processing, and pattern recognition"-- |
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Deep learning in computer vision principles and applications edited by M. Hassaballah and Ali Ismail Awad, Boca Raton London New York CRC Press, Taylor & Francis Group [2020], © 2020, xvi, 322 Seiten Illustrationen, Diagramme, Text txt rdacontent, ohne Hilfsmittel zu benutzen n rdamedia, Band nc rdacarrier, Digital imaging and computer vision series, Includes bibliographical references and index, "Deep learning algorithms have brought a revolution to the computer vision community by introducing non-traditional and efficient solutions to several image-related problems that had long remained unsolved or partially addressed. This book presents a collection of eleven chapters where each individual chapter explains the deep learning principles of a specific topic, introduces reviews of up-to-date techniques, and presents research findings to the computer vision community. The book covers a broad scope of topics in deep learning concepts and applications such as accelerating the convolutional neural network inference on field-programmable gate arrays, fire detection in surveillance applications, face recognition, action and activity recognition, semantic segmentation for autonomous driving, aerial imagery registration, robot vision, tumor detection, and skin lesion segmentation as well as skin melanoma classification. The content of this book has been organized such that each chapter can be read independently from the others. The book is a valuable companion for researchers, postgraduate and possibly senior undergraduate students who are taking an advanced course in related topics, and for those who are interested in deep learning with applications in computer vision, image processing, and pattern recognition"--, Computer vision, Machine learning, Aufsatzsammlung (DE-588)4143413-4 (DE-627)105605727 (DE-576)209726091 gnd-content, s (DE-588)4129594-8 (DE-627)10570878X (DE-576)209611812 Maschinelles Sehen gnd, s (DE-588)1135597375 (DE-627)890512922 (DE-576)489847412 Deep learning gnd, s (DE-588)4193754-5 (DE-627)105224782 (DE-576)21008944X Maschinelles Lernen gnd, s (DE-588)4207417-4 (DE-627)10512026X (DE-576)210180714 Computervision gnd, (DE-627), Hassaballah, Mahmoud 1974- HerausgeberIn (DE-588)1091568073 (DE-627)852456980 (DE-576)461716852 edt, Awad, Ali Ismail HerausgeberIn (DE-588)1091567212 (DE-627)852455631 (DE-576)461715724 edt, 9781351003827, Erscheint auch als Online-Ausgabe Deep learning in computer vision Boca Raton, FL : CRC Press/Taylor and Francis, 2020 (DLC)2019057833, Erscheint auch als Online-Ausgabe Deep learning in computer vision Boca Raton : CRC Press, 2020 1 Online-Ressource (xvi, 322 Seiten) (DE-627)1737743019 9781351003827 1351003828 9781351003810 135100381X 9781351003803 1351003801 9781351003797 1351003798, https://www.gbv.de/dms/tib-ub-hannover/1689812125.pdf V:DE-601 B:DE-89 pdf/application Inhaltsverzeichnis |
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Deep learning in computer vision: principles and applications, "Deep learning algorithms have brought a revolution to the computer vision community by introducing non-traditional and efficient solutions to several image-related problems that had long remained unsolved or partially addressed. This book presents a collection of eleven chapters where each individual chapter explains the deep learning principles of a specific topic, introduces reviews of up-to-date techniques, and presents research findings to the computer vision community. The book covers a broad scope of topics in deep learning concepts and applications such as accelerating the convolutional neural network inference on field-programmable gate arrays, fire detection in surveillance applications, face recognition, action and activity recognition, semantic segmentation for autonomous driving, aerial imagery registration, robot vision, tumor detection, and skin lesion segmentation as well as skin melanoma classification. The content of this book has been organized such that each chapter can be read independently from the others. The book is a valuable companion for researchers, postgraduate and possibly senior undergraduate students who are taking an advanced course in related topics, and for those who are interested in deep learning with applications in computer vision, image processing, and pattern recognition"--, Computer vision, Machine learning, Aufsatzsammlung, Maschinelles Sehen, Deep learning, Maschinelles Lernen, Computervision |
| title |
Deep learning in computer vision: principles and applications |
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Deep learning in computer vision principles and applications |
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Deep learning in computer vision principles and applications edited by M. Hassaballah and Ali Ismail Awad |
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Deep learning in computer vision principles and applications edited by M. Hassaballah and Ali Ismail Awad |
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Deep learning in computer vision principles and applications edited by M. Hassaballah and Ali Ismail Awad |
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Deep learning in computer vision |
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deep learning in computer vision principles and applications |
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principles and applications |
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Deep learning in computer vision: principles and applications |
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Computer vision, Machine learning, Aufsatzsammlung, Maschinelles Sehen, Deep learning, Maschinelles Lernen, Computervision |
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Computer vision, Machine learning, Aufsatzsammlung, Maschinelles Sehen, Deep learning, Maschinelles Lernen, Computervision |
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