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Deep learning in computer vision :principles and applications /

紀錄類型:	書目-語言資料,印刷品 : 單行本
正題名/作者:	Deep learning in computer vision :/ edited by M. Hassaballah and Ali Ismail Awad.
其他題名:	principles and applications /
其他作者:	Hassaballah, Mahmoud,
出版者:	Boca Raton, FL :CRC Press/Taylor and Francis,c2020.
面頁冊數:	xvi, 322 p. :ill. (some col.) ;24 cm.
標題:	Computer vision. -
ISBN:	9781138544420 (hbk.) :

Deep learning in computer vision :principles and applications /
Deep learning in computer vision :principles and applications /edited by M. Hassaballah and Ali Ismail Awad. - 1st ed. - Boca Raton, FL :CRC Press/Taylor and Francis,c2020. - xvi, 322 p. :ill. (some col.) ;24 cm. - Digital imaging and computer vision.

Includes bibliographical references and index.

"Deep learning algorithms have brought a revolution to the computer vision community by introducing non-traditional and efficient solutions toseveral image-related problems that had long remained unsolved or partiallyaddressed. This book presents a collection of eleven chapters where eachindividual chapter explains the deep learning principles of a specifictopic, introduces reviews of up-to-date techniques, and presents researchfindings to the computer vision community. The book covers a broad scope oftopics in deep learning concepts and applications such as accelerating theconvolutional neural network inference on field-programmable gate arrays,fire detection in surveillance applications, face recognition, action andactivity recognition, semantic segmentation for autonomous driving, aerialimagery registration, robot vision, tumor detection, and skin lesionsegmentation as well as skin melanoma classification. The content of thisbook has been organized such that each chapter can be read independentlyfrom the others. The book is a valuable companion for researchers,postgraduate and possibly senior undergraduate students who are taking anadvanced course in related topics, and for those who are interested in deeplearning with applications in computer vision, image processing, and patternrecognition"--

ISBN: 9781138544420 (hbk.) :NT2743

LCCN: 2019057832Subjects--Topical Terms:

148528
Computer vision.

LC Class. No.: TA1634 / .D437 2020

Dewey Class. No.: 006.3/7

Deep learning in computer vision :principles and applications /
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245 0 0 $a Deep learning in computer vision : $b principles and applications / $c edited by M. Hassaballah and Ali Ismail Awad.
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260 # $a Boca Raton, FL : $b CRC Press/Taylor and Francis, $c c2020.
300 $a xvi, 322 p. : $b ill. (some col.) ; $c 24 cm.
490 0 $a Digital imaging and computer vision
504 $a Includes bibliographical references and index.
520 # $a "Deep learning algorithms have brought a revolution to the computer vision community by introducing non-traditional and efficient solutions toseveral image-related problems that had long remained unsolved or partiallyaddressed. This book presents a collection of eleven chapters where eachindividual chapter explains the deep learning principles of a specifictopic, introduces reviews of up-to-date techniques, and presents researchfindings to the computer vision community. The book covers a broad scope oftopics in deep learning concepts and applications such as accelerating theconvolutional neural network inference on field-programmable gate arrays,fire detection in surveillance applications, face recognition, action andactivity recognition, semantic segmentation for autonomous driving, aerialimagery registration, robot vision, tumor detection, and skin lesionsegmentation as well as skin melanoma classification. The content of thisbook has been organized such that each chapter can be read independentlyfrom the others. The book is a valuable companion for researchers,postgraduate and possibly senior undergraduate students who are taking anadvanced course in related topics, and for those who are interested in deeplearning with applications in computer vision, image processing, and patternrecognition"-- $c Provided by publisher.
650 # 0 $a Computer vision. $3 148528
650 # 0 $a Machine learning. $3 147118
700 1 # $a Hassaballah, Mahmoud, $e editor. $3 1000140490
700 1 # $a Awad, Ali Ismail, $e editor. $3 1000140489
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