02819nam a2200325   4500999001500000001000600015003000900021005001700030008004100047020004900088020004200137040004300179082001800222245011700240250001900357264005600376300004600432490004000478504005100518520136400569650002101933650002201954650003701976700003502013700003102048776012502079942001202204952012502216952015202341  c8356d835621865BD-DhUAP20230810153815.0191212s2020    flua     b    001 0 eng    a9781138544420q(hardback ;qacid-free paper)  z9781351003827q(ebook)a9781032242859  aDLCbEngeBD-DhUAPcBD-DhUAPdBD-DhUAP00a006.3 DEE22300aDeep learning in computer vision :bprinciples and applications /cedited by M. Hassaballah and Ali Ismail Awad.  aFirst edition. 1aBoca Raton :bCRC Press/Taylor and Francis,c[2020]  axvi, 322 pages :billustrations ;c24 cm.0 aDigital imaging and computer vision  aIncludes bibliographical references and index.  a"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"--cProvided by publisher. 0aComputer vision. 0aMachine learning. 0aDeep learning (Machine learning)1 aHassaballah, Mahmoud,eeditor.1 aAwad, Ali Ismail,eeditor.08iOnline version:tDeep learning in computer visionbFirst edition.dBoca Raton, FL : CRC Press/Taylor and Francis,  2020.  2ddccBK  00102ddc4070aUAPCLbUAPCLcGeneral Stacksd2023-08-10o006.3 DEEp3010021865r2023-08-10t1v5030.00w2023-08-10yBK  00102ddc4070aUAPCLbUAPCLcGeneral Stacksd2023-08-10l2o006.3 DEEp3010021866q2025-01-11r2024-12-28s2024-12-28t2v5030.00w2023-08-10yBK