Deep Learning in Computer Vision: Principles and Applications

Author:   Mahmoud Hassaballah ,  Ali Ismail Awad
Publisher:   Taylor & Francis Ltd
ISBN:  

9781138544420


Pages:   322
Publication Date:   07 April 2020
Format:   Hardback
Availability:   In Print   Availability explained
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Deep Learning in Computer Vision: Principles and Applications


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Author:   Mahmoud Hassaballah ,  Ali Ismail Awad
Publisher:   Taylor & Francis Ltd
Imprint:   CRC Press
Weight:   0.653kg
ISBN:  

9781138544420


ISBN 10:   1138544426
Pages:   322
Publication Date:   07 April 2020
Audience:   College/higher education ,  Undergraduate ,  Postgraduate, Research & Scholarly
Format:   Hardback
Publisher's Status:   Active
Availability:   In Print   Availability explained
This item will be ordered in for you from one of our suppliers. Upon receipt, we will promptly dispatch it out to you. For in store availability, please contact us.

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Mahmoud Hassaballah received the Doctor of Engineering (D. Eng.) in Computer Science from Ehime University, Japan in 2011. He was a visiting scholar with the Department of Computer & Communication Science, Wakayama University, Japan and GREAH laboratory, Le Havre Normandie University, France. He is currently an Associate Professor of Computer Science at the Faculty of Computers and Information, South Valley University, Egypt. His research interests include feature extraction, object detection/recognition, artificial intelligence, biometrics, image processing, computer vision, machine learning, and data hiding. Ali Ismail Awad is currently an Associate Professor (Docent) with the Department of Computer Science, Electrical and Space Engineering, Luleå University of Technology, Luleå, Sweden, where he also serves as a Coordinator of the Master Programme in Information Security. He is a Visiting Researcher with the University of Plymouth, United Kingdom. He is also an Associate Professor with the Electrical Engineering Department, Faculty of Engineering, Al-Azhar University at Qena, Qena, Egypt. His research interests include information security, Internet-of-Things security, image analysis with applications in biometrics and medical imaging, and network security.

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