Visual quality assessment by machine learning [electronic resource] / Long Xu, Weisi Lin, C.-C. Jay Kuo.
Xu, Long, author.; Lin, Weisi, author.; Kuo, C.-C. Jay (Chung-Chieh Jay), author.
2015
Q325.5
Available Online

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Title Visual quality assessment by machine learning [electronic resource] / Long Xu, Weisi Lin, C.-C. Jay Kuo.
Author Xu, Long, author.
ISBN 9789812874689 electronic book
9812874682 electronic book
9789812874672
DOI https://doi.org/10.1007/978-981-287-468-9
Published Singapore : Springer, 2015.
Language English
Description 1 online resource (xiv, 132 pages) : illustrations.
Other Standard Identifiers 10.1007/978-981-287-468-9 doi
Call Number Q325.5
Dewey Decimal Classification 006.3/1
Summary 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.
Bibliography, etc. Note Includes bibliographical references.
Access Note Access limited to authorized users.
Source of Description Online resource; title from PDF title page (SpringerLink, viewed May 14, 2015).
Added Author Lin, Weisi, author.
Kuo, C.-C. Jay (Chung-Chieh Jay), author.
Series SpringerBriefs in electrical and computer engineering. Signal processing.
Available in Other Form Print version: 9789812874672
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Introduction
Fundamental knowledges of machine learning
Image features and feature processing
Feature pooling by learning
Metrics fusion
Summary and remarks for future research.

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