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Visual Quality Assessment by Machine Learning (2015)

Contributor(s): Xu, Long (Author), Lin, Weisi (Author), Kuo, C -C Jay (Author)

ISBN: 9789812874672

Publisher: Springer

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Pub Date: May 27, 2015

Dewey: 006.31

Lexile Code: 0000

Features: Illustrated

Target Age Group: NA to NA

Physical Info: 0.32" H x 9.21" L x 6.14" W ( 0.48 lbs) 132 pages

Series: Springerbriefs in Electrical and Computer Engineering / Spri

Descriptions, Reviews, etc.

Description: The book encompasses the state-of-the-art visual quality assessment (VQA) and learning based visual quality assessment (LB-VQA) by providing a comprehensive overview of the existing relevant methods. It delivers the readers the basic knowledge, systematic overview and new development of VQA. It also encompasses the preliminary knowledge of Machine Learning (ML) to VQA tasks and newly developed ML techniques for the purpose. Hence, firstly, it is particularly helpful to the beginner-readers (including research students) to enter into VQA field in general and LB-VQA one in particular. Secondly, new development in VQA and LB-VQA particularly are detailed in this book, which will give peer researchers and engineers new insights in VQA.

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