Visual Quality Assessment by Machine Learning

Long Xu, Weisi Lin, C.-C. Jay Kuo (Autoren)

Buch | Softcover

132 Seiten

2015 | 2015 ed.
Springer Verlag, Singapore
978-981-287-467-2 (ISBN)

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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.

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

Reihe/Serie	SpringerBriefs in Electrical and Computer Engineering
Reihe/Serie	SpringerBriefs in Signal Processing
Zusatzinfo	16 Illustrations, color; 3 Illustrations, black and white; XIV, 132 p. 19 illus., 16 illus. in color.
Verlagsort	Singapore
Sprache	englisch
Maße	155 x 235 mm
Themenwelt	Informatik ► Grafik / Design ► Digitale Bildverarbeitung
	Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik
	Technik ► Elektrotechnik / Energietechnik
Schlagworte	Feature Selection • machine learning • Rank Learning • support vector learning • Visual Quality Assessment (VQA)
ISBN-10	981-287-467-4 / 9812874674
ISBN-13	978-981-287-467-2 / 9789812874672
Zustand	Neuware