Visual Quality Assessment by Machine Learning - Long Xu, Weisi Lin, C.-C. Jay Kuo

Visual Quality Assessment by Machine Learning

Buch | Softcover
132 Seiten
2015 | 2015 ed.
Springer Verlag, Singapore
978-981-287-467-2 (ISBN)
53,49 inkl. MwSt
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
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
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