Deep learning in computer vision[electronic resource] :principles and applications
- 其他作者: Hassaballah, Mahmoud. , Awad, Ali Ismail.
- 出版: Boca Raton, FL : CRC Press c2020.
- 稽核項: 1 online resource.
- 叢書名: Digital imaging and computer vision series
- 標題: Computer vision. , Machine learning.
- ISBN: 1351003828 , 9781351003827
- ISBN: 9781138544420
- 試查全文@TNUA:
- 附註: Includes bibliographical references and index.
- 摘要: "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"--
- 電子資源: https://dbs.tnua.edu.tw/login?url=https://www.taylorfrancis.com/books/9781351003827
- 系統號: 005325916
- 資料類型: 電子書
- 讀者標籤: 需登入
- 引用網址: 複製連結
"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"--
來源: Google Book
來源: Google Book
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