Visual Quality Assessment by Machine Learning (SpringerBriefs in Electrical and Computer Engineering)

Long Xu, Weisi Lin, C.-C. Jay Kuo

ISBN 10: 9812874674 / ISBN 13: 9789812874672

Editore: Springer 2015-05-31, 2015

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Codice articolo 6666-IUK-9789812874672

Dati bibliografici

• Titolo: Visual Quality Assessment by Machine Learning (SpringerBriefs in Electrical and Computer Engineering)
• Editore: Springer 2015-05-31
• Data di pubblicazione: 2015
• Lingua: Inglese
• ISBN 10: 9812874674
• ISBN 13: 9789812874672
• Rilegatura: Paperback
• Condizione: New

Descrizione articolo

Riassunto

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.

Contenuti

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