Visual quality assessment by machine learning [electronic resource] / Long Xu, Weisi Lin, C.-C. Jay Kuo.

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Visual quality assessment by machine learning [electronic resource] / Long Xu, Weisi Lin, C.-C. Jay Kuo.

9789812874689 electronic book
9812874682 electronic book
9789812874672

Singapore : Springer, 2015.

English

1 online resource (xiv, 132 pages) : illustrations.

10.1007/978-981-287-468-9 doi

Q325.5

006.3/1

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.

Includes bibliographical references.

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Online resource; title from PDF title page (SpringerLink, viewed May 14, 2015).

SpringerBriefs in electrical and computer engineering. Signal processing.

Print version: 9789812874672

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