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Visual quality assessment by machine learning [electronic resource]

자료유형

E-Book(소장)

개인저자

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

서명 / 저자사항

Visual quality assessment by machine learning [electronic resource] / Long Xu, Weisi Lin, C.-C. Jay Kuo.

발행사항

Singapore : Springer Singapore : Imprint: Springer, 2015.

형태사항

1 online resource (xiv, 132 p.) : ill. (some col.).

총서사항

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.

일반주기

Title from e-Book title page.

내용주기

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

서지주기

Includes bibliographical references.

이용가능한 다른형태자료

Issued also as a book.

일반주제명

Machine learning. Image processing --Digital techniques.

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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)

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No.	소장처	청구기호	등록번호	도서상태	반납예정일	예약	서비스
No. 1	소장처 중앙도서관/e-Book 컬렉션/	청구기호 CR 006.31	등록번호 E14030444	도서상태 대출불가(열람가능)	반납예정일	예약	서비스 M

Visual quality assessment by machine learning [electronic resource]

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