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Herausgeber: 
  • Ali Ismail Awad
  • Mahmoud Hassaballah
  • Deep Learning in Computer Vision: Principles and Applications 
     

    (Buch)
    Dieser Artikel gilt, aufgrund seiner Grösse, beim Versand als 3 Artikel!


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   i.d.R. innert 14-24 Tagen versandfertig
    Veröffentlichung:  April 2020  
    Genre:  EDV / Informatik 
    ISBN:  9781138544420 
    EAN-Code: 
    9781138544420 
    Verlag:  CRC Press 
    Einband:  Gebunden  
    Sprache:  English  
    Serie:  Digital Imaging and Computer Vision  
    Dimensionen:  H 239 mm / B 160 mm / D 25 mm 
    Gewicht:  612 gr 
    Seiten:  322 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:
    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.

      
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