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Visual quality assessment by machine learning [electronic resource]

Visual quality assessment by machine learning [electronic resource]

Material type
E-Book(소장)
Personal Author
Xu, Long. Lin, Weisi. Kuo, C.-C. Jay (Chung-Chieh Jay).
Title Statement
Visual quality assessment by machine learning [electronic resource] / Long Xu, Weisi Lin, C.-C. Jay Kuo.
Publication, Distribution, etc
Singapore :   Springer Singapore :   Imprint: Springer,   2015.  
Physical Medium
1 online resource (xiv, 132 p.) : ill. (some col.).
Series Statement
SpringerBriefs in electrical and computer engineering,2191-8112
ISBN
9789812874689
요약
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.
General Note
Title from e-Book title page.  
Content Notes
Introduction -- Fundamental knowledges of machine learning -- Image features and feature processing -- Feature pooling by learning -- Metrics fusion -- Summary and remarks for future research.
Bibliography, Etc. Note
Includes bibliographical references.
이용가능한 다른형태자료
Issued also as a book.  
Subject Added Entry-Topical Term
Machine learning. Image processing --Digital techniques.
Short cut
URL
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020 ▼a 9789812874689
040 ▼a 211009 ▼c 211009 ▼d 211009
050 4 ▼a Q325.5
082 0 4 ▼a 006.31 ▼2 23
084 ▼a 006.31 ▼2 DDCK
090 ▼a 006.31
100 1 ▼a Xu, Long.
245 1 0 ▼a Visual quality assessment by machine learning ▼h [electronic resource] / ▼c Long Xu, Weisi Lin, C.-C. Jay Kuo.
260 ▼a Singapore : ▼b Springer Singapore : ▼b Imprint: Springer, ▼c 2015.
300 ▼a 1 online resource (xiv, 132 p.) : ▼b ill. (some col.).
490 1 ▼a SpringerBriefs in electrical and computer engineering, ▼x 2191-8112
500 ▼a Title from e-Book title page.
504 ▼a Includes bibliographical references.
505 0 ▼a Introduction -- Fundamental knowledges of machine learning -- Image features and feature processing -- Feature pooling by learning -- Metrics fusion -- Summary and remarks for future research.
520 ▼a 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.
530 ▼a Issued also as a book.
538 ▼a Mode of access: World Wide Web.
650 0 ▼a Machine learning.
650 0 ▼a Image processing ▼x Digital techniques.
700 1 ▼a Lin, Weisi.
700 1 ▼a Kuo, C.-C. Jay ▼q (Chung-Chieh Jay).
830 0 ▼a SpringerBriefs in electrical and computer engineering.
856 4 0 ▼u https://oca.korea.ac.kr/link.n2s?url=http://dx.doi.org/10.1007/978-981-287-468-9
945 ▼a KLPA
991 ▼a E-Book(소장)

Holdings Information

No. Location Call Number Accession No. Availability Due Date Make a Reservation Service
No. 1 Location Main Library/e-Book Collection/ Call Number CR 006.31 Accession No. E14030444 Availability Loan can not(reference room) Due Date Make a Reservation Service M

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