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 br…
Read More ↓Title Statements
- Full title :Deep learning in computer vision : principles and applications / edited by Mahmoud Hassaballad and Ali Ismail Awad.
Summary
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, for 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.
Read More ↓Edition Statements
- Publication Date:2020.
Publication Statements
- Publisher(s):CRC Press
- Place of Publication:Boca Raton, FL
- Language:eng
- Publication Date:2020.
Notes
Description d'après la consultation du 2020-12-02.
Titre provenant de la page de titre du document numérisé.
Edition électronique diffusée simultanément à l'édition imprimée.
La pagination de l'édition imprimée correspondante est de : XVI-322 p.
The Physical Object
- Description:1 online resource.
Edition Identifiers
- ISBN:9781351003827 (PDF), 1351003828 (PDF)
- oclc:on1225197926
- Dewey Decimal:006.37
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