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Computer Vision Metrics [electronic resource] : survey, taxonomy and analysis of computer vision, visual neuroscience, and deep learning / Textbook ed

Computer Vision Metrics [electronic resource] : survey, taxonomy and analysis of computer vision, visual neuroscience, and deep learning / Textbook ed

Material type
E-Book(소장)
Personal Author
Krig, Scott.
Title Statement
Computer Vision Metrics [electronic resource] : survey, taxonomy and analysis of computer vision, visual neuroscience, and deep learning / by Scott Krig.
판사항
Textbook ed.
Publication, Distribution, etc
Cham :   Springer International Publishing :   Imprint: Springer,   2016.  
Physical Medium
1 online resource (xviii, 637 p.) : ill. (some col.).
ISBN
9783319337623
요약
Based on the successful 2014 book published by Apress, this textbook edition is expanded to provide a comprehensive history and state-of-the-art survey for fundamental computer vision methods. With over 800 essential references, as well as chapter-by-chapter learning assignments, both students and researchers can dig deeper into core computer vision topics. The survey covers everything from feature descriptors, regional and global feature metrics, feature learning architectures, deep learning, neuroscience of vision, neural networks, and detailed example architectures to illustrate computer vision hardware and software optimization methods. To complement the survey, the textbook includes useful analyses which provide insight into the goals of various methods, why they work, and how they may be optimized. The text delivers an essential survey and a valuable taxonomy, thus providing a key learning tool for students, researchers and engineers, to supplement the many effective hands-on resources and open source projects, such as OpenCVand other imaging and deep learning tools.
General Note
Title from e-Book title page.  
Content Notes
Image Capture and Representation -- Image Re-processing -- Global and Regional Features -- Local Feature Design Concepts -- Taxonomy of Feature Description Attributes -- Interest Point Detector and Feature Descriptor Survey -- Ground Truth Data, Content, Metrics, and Analysis -- Vision Pipeline and Optimizations -- Feature Learning Architecture Taxonomy and Neuroscience Background -- Feature Learning and Deep Learning Architecture Survey. .
Bibliography, Etc. Note
Includes bibliographical references and index.
이용가능한 다른형태자료
Issued also as a book.  
Subject Added Entry-Topical Term
Computer vision.
Short cut
URL
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020 ▼a 9783319337623
040 ▼a 211009 ▼c 211009 ▼d 211009
082 0 4 ▼a 006.37 ▼2 23
084 ▼a 006.37 ▼2 DDCK
090 ▼a 006.37
100 1 ▼a Krig, Scott.
245 1 0 ▼a Computer Vision Metrics ▼h [electronic resource] : ▼b survey, taxonomy and analysis of computer vision, visual neuroscience, and deep learning / ▼c by Scott Krig.
250 ▼a Textbook ed.
260 ▼a Cham : ▼b Springer International Publishing : ▼b Imprint: Springer, ▼c 2016.
300 ▼a 1 online resource (xviii, 637 p.) : ▼b ill. (some col.).
500 ▼a Title from e-Book title page.
504 ▼a Includes bibliographical references and index.
505 0 ▼a Image Capture and Representation -- Image Re-processing -- Global and Regional Features -- Local Feature Design Concepts -- Taxonomy of Feature Description Attributes -- Interest Point Detector and Feature Descriptor Survey -- Ground Truth Data, Content, Metrics, and Analysis -- Vision Pipeline and Optimizations -- Feature Learning Architecture Taxonomy and Neuroscience Background -- Feature Learning and Deep Learning Architecture Survey. .
520 ▼a Based on the successful 2014 book published by Apress, this textbook edition is expanded to provide a comprehensive history and state-of-the-art survey for fundamental computer vision methods. With over 800 essential references, as well as chapter-by-chapter learning assignments, both students and researchers can dig deeper into core computer vision topics. The survey covers everything from feature descriptors, regional and global feature metrics, feature learning architectures, deep learning, neuroscience of vision, neural networks, and detailed example architectures to illustrate computer vision hardware and software optimization methods. To complement the survey, the textbook includes useful analyses which provide insight into the goals of various methods, why they work, and how they may be optimized. The text delivers an essential survey and a valuable taxonomy, thus providing a key learning tool for students, researchers and engineers, to supplement the many effective hands-on resources and open source projects, such as OpenCVand other imaging and deep learning tools.
530 ▼a Issued also as a book.
538 ▼a Mode of access: World Wide Web.
650 0 ▼a Computer vision.
856 4 0 ▼u https://oca.korea.ac.kr/link.n2s?url=http://dx.doi.org/10.1007/978-3-319-33762-3
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 006.37 Accession No. E14022414 Availability Loan can not(reference room) Due Date Make a Reservation Service M

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