Visual quality assessment by machine learning [electronic resource]

• 作者： Xu, Long.
• 其他作者：
  • Lin, Weisi.
  • Kuo, C.-C. Jay.
  • SpringerLink (Online service)
• 其他題名：
  • SpringerBriefs in electrical and computer engineering.
• 出版： Singapore : Springer Singapore :Imprint: Springer
• 叢書名： SpringerBriefs in electrical and computer engineering, Signal processing,
• 主題： Machine learning , Image processing--Digital techniques , Engineering , Signal, Image and Speech Processing. , Image Processing and Computer Vision. , Computational intelligence
• ISBN： 9789812874689 (electronic bk.) 、 9789812874672 (paper)
• FIND@SFXID: CGU
• 資料類型: 電子書
• 內容註: Introduction -- Fundamental knowledges of machine learning -- Image features and feature processing -- Feature pooling by learning -- Metrics fusion -- Summary and remarks for future research.
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• 摘要註: 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.
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