Visual Quality Assessment by Machine Learning (Paperback, 2015 ed.)

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.

General

Imprint:	Springer Verlag, Singapore
Country of origin:	Singapore
Series:	SpringerBriefs in Signal Processing
Release date:	May 2015
First published:	2015
Authors:	Long Xu • Weisi Lin • C.-C.Jay Kuo
Dimensions:	235 x 155 x 8mm (L x W x T)
Format:	Paperback
Pages:	132
Edition:	2015 ed.
ISBN-13:	978-981-287-467-2
Categories:	Books > Computing & IT > Applications of computing > Artificial intelligence > Machine learning Books > Computing & IT > Applications of computing > Image processing > General Books > Professional & Technical > Electronics & communications engineering > Electronics engineering > Applied optics > General
LSN:	981-287-467-4
Barcode:	9789812874672

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