Call for Chapters

 

Deep Learning in Computer Vision: Theories and Applications

 

 

Aims and Scope:

Recent advances in learning algorithms for deep architectures have made deep learning feasible and deep learning systems have achieved state-of-the-art performance and sometimes show superior performance on fully supervised learning tasks on several fields. Specifically, deep learning algorithms have brought a revolution to the computer vision community, introducing non-traditional and efficient solutions to several image-related problems that had long remained unsolved. Today, utilizing deep learning-based methods in computer vision is a very hot topic. For some tasks such as object recognition and image classification, tremendous progress has been made in applying deep learning techniques. On the other hand, there are some debates as to the reasons for the high success of the deep learning-based methods, and about the limitations of these methods. Besides, several questions are still open and need answers as to how these methods can be tailored to certain computer vision tasks such as videos-related applications and how to scale up the models and training data. Topics of interest include, but are not limited to:

 

Deep Learning Theories

Deep Learning Applications

 

Publication Schedule:

The tentative schedule of the book publication is as follows:

 

Submission Procedure:

Authors are invited to submit original, high quality, unpublished results of both deep learning theories and applications in the computer vision domain. Prospective authors need to electronically submit their contributions using EasyChair submission system (Link). Submitted manuscripts will be refereed by at least two independent and expert reviewers for quality, correctness, originality, and relevance. The accepted contributions will be published as a book in the prestigious Digital Imaging and Computer Vision Book Series by CRC Press. More information about the "Digital Imaging and Computer Vision Book Series" can be found in the (Link). Please consider the following points when preparing your manuscript:

 

Book Editors:

Dr.: M. Hassaballah, (ResearchGate, Google Scholar)
Department of Computer Science,
Faculty of Computers and Information
South Valley University, Luxor, Egypt
E-mail: m.hassaballah[at]svu.edu.eg

 

Dr.: Ali Ismail Awad (ResearchGate, Google Scholar)
Department of Computer Science, Electrical and Space Engineering
Luleå University of Technology
Luleå, Sweden
E-mail: ali.awad[at]ltu.se

 

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