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Visual quality assessment by machine learning[electronic resource] /

紀錄類型:	書目-電子資源 : Monograph/item
杜威分類號:	006.31
書名/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.
出版者:	Singapore : : Springer Singapore :, 2015.
面頁冊數:	xiv, 132 p. : : ill., digital ;; 24 cm.
Contained By:	Springer eBooks
標題:	Machine learning.
標題:	Image processing - Digital techniques.
標題:	Engineering.
標題:	Signal, Image and Speech Processing.
標題:	Image Processing and Computer Vision.
標題:	Computational Intelligence.
ISBN:	9789812874689 (electronic bk.)
ISBN:	9789812874672 (paper)
內容註:	Introduction -- Fundamental knowledges of machine learning -- Image features and feature processing -- Feature pooling by learning -- Metrics fusion -- Summary and remarks for future research.
摘要、提要註:	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.
電子資源:	http://dx.doi.org/10.1007/978-981-287-468-9

Visual quality assessment by machine learning[electronic resource] /
Xu, Long.

Visual quality assessment by machine learning[electronic resource] /by Long Xu, Weisi Lin, C.-C. Jay Kuo. - Singapore :Springer Singapore :2015. - xiv, 132 p. :ill., digital ;24 cm. - SpringerBriefs in electrical and computer engineering, Signal processing,2191-8112. - SpringerBriefs in electrical and computer engineering.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 (electronic bk.)

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

202931
Machine learning.

LC Class. No.: Q325.5

Dewey Class. No.: 006.31

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