國立虎尾科技大學 |

Visual Quality Assessment by Machine Learning

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Visual Quality Assessment by Machine Learning/ by Long Xu, Weisi Lin, C.-C. Jay Kuo.
作者:	Xu, Long.
其他作者:	Lin, Weisi.
面頁冊數:	XIV, 132 p. 19 illus., 16 illus. in color.online resource. :
Contained By:	Springer Nature eBook
標題:	Signal processing. -
電子資源:	https://doi.org/10.1007/978-981-287-468-9
ISBN:	9789812874689

Visual Quality Assessment by Machine Learning
Xu, Long.

Visual Quality Assessment by Machine Learning[electronic resource] /by Long Xu, Weisi Lin, C.-C. Jay Kuo. - 1st ed. 2015. - XIV, 132 p. 19 illus., 16 illus. in color.online resource. - SpringerBriefs in Signal Processing,2196-4076. - SpringerBriefs in Signal Processing,.

Introduction -- Fundamental knowledges of machine learning -- Image features and feature processing -- Feature pooling by learning -- Metrics fusion -- Summary and remarks for future research.

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.

ISBN: 9789812874689

Standard No.: 10.1007/978-981-287-468-9doiSubjects--Topical Terms:

561459
Signal processing.

LC Class. No.: TK5102.9

Dewey Class. No.: 621.382

Visual Quality Assessment by Machine Learning
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