Visual Quality Assessment by Machine Learning

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53,49 €

SpringerBriefs in Electrical and Computer Engineering – SpringerBriefs in Signal Processing

ISBN: 9812874674
ISBN 13: 9789812874672
Autor: Xu, Long/Lin, Weisi/Kuo, C -C Jay
Verlag: Springer Verlag GmbH
Umfang: xiv, 132 S., 3 s/w Illustr., 16 farbige Illustr., 132 p. 19 illus., 16 illus. in color.
Erscheinungsdatum: 27.05.2015
Auflage: 1/2015
Produktform: Kartoniert
Einband: Kartoniert

Presents the emerging techniques of learning based visual quality assessmentHighlights machine learning techniques and their applications in visual quality assessmentIncludes a number of real-world examples that readers can implement in their own workIncludes supplementary material: sn.pub/extras

Artikelnummer: 7828617 Kategorie:

Beschreibung

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.

Herstellerkennzeichnung:


Springer Verlag GmbH
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69121 Heidelberg
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E-Mail: juergen.hartmann@springer.com

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