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Synopsis
Some of the fundamental constraints of automated machine vision have been the inability automatically to adapt parameter settings or utilize previous adaptations in changing environments. Symbolic Visual Learning presents research which adds visual learning capabilities to computer vision systems. Using this state-of-the-art recognition technology, the outcome is different adaptive recognition systems that can measure their own performance, learn from their experience and outperform conventional static designs. Written as a companion volume to Early Visual Learning (edited by S. Nayar and T. Poggio), this book is intended for researchers and students in machine vision and machine learning.
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Synopsis
Some of the fundamental constraints of automated machine vision have been the inability automatically to adapt parameter settings or utilize previous adaptations in changing environments. This work presents research which adds visual learning capabilities to computer vision systems. Using this state-of-the-art recognition technology, the outcome is different adaptive recognition systems that can measure their own performance, learn from their experience and outperform conventional static designs. The book was written as a companion volume to "Early Visual Learning".
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Symbolic Visual Learning
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Oxford University Press, Incorporated, 1997
ISBN 10: 0195098706
ISBN 13: 9780195098709
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Symbolic Visual Learning
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Oxford University Press, 1997
ISBN 10: 0195098706
ISBN 13: 9780195098709
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Symbolic visual learning.
Published by
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ISBN 10: 0195098706
ISBN 13: 9780195098709
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Condition: very good. New York & Oxford : Oxford University Press, 1997, Hardcover. Viii, 355p : ill ; 27cm. Companion volume to: Early visual learning. Includes bibliographical references and index. - Some of the fundamental constraints of automated machine vision have been the inability to automatically adapt parameter settings or utilize previous adaptations in changing environments. Symbolic Visual Learning presents research which adds visual learning capabilities to computer vision systems. Using this state-of-the-art recognition technology, the outcome is different adaptive recognition systems that can measure their own performance, learn from their experience and outperform conventional static designs. Written as a companion volume to Early Visual Learning (edited by S. Nayar and T. Poggio), this book is intended for researchers and students in machine vision and machine learning. Condition : very good copy. ISBN 9780195098709. Keywords : PSYCHOLOGY, Seller Inventory # 204494
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Symbolic Visual Learning
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Oxford University Press, USA, 1997
ISBN 10: 0195098706
ISBN 13: 9780195098709
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Symbolic Visual Learning
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ISBN 10: 0195098706
ISBN 13: 9780195098709
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Condition: New. This work presents research which adds visual learning capabilities to computer vision systems. Using this recognition technology, the outcome is different adaptive recognition systems that can measure their own performance, learn from their experience and outperform conventional static designs. Editor(s): Ikeuchi, Katsuchi; Veloso, Manuela M.; Velosa, Manuela. Num Pages: 368 pages, halftone and line figures, tables. BIC Classification: UYQN; UYQV. Category: (P) Professional & Vocational; (UP) Postgraduate, Research & Scholarly; (UU) Undergraduate. Dimension: 263 x 185 x 22. Weight in Grams: 825. . 1997. Hardback. . . . . Seller Inventory # V9780195098709
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Symbolic Visual Learning
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Condition: Sehr gut. Zustand: Sehr gut | Seiten: 368 | Sprache: Englisch | Produktart: Bücher | Some of the fundamental constraints of automated machine vision have been the inability automatically to adapt parameter settings or utilize previous adaptations in changing environments. Symbolic Visual Learning, as presented in this book, consists of an area of research that tries to overcome these fundamental constraints, enhancing state-of-the-art recognition systems that can measure their own performance, learn from their experience, and outperform conventional static designs. It was written as a companion volume to Early Visual Learning edited by S. Nayar and T. Poggio. Seller Inventory # 10050240/202
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Symbolic Visual Learning
Published by
Oxford University Press, USA, 1997
ISBN 10: 0195098706
ISBN 13: 9780195098709
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Symbolic Visual Learning (eng)
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Symbolic Visual Learning
Published by
Oxford University Press Inc, 1997
ISBN 10: 0195098706
ISBN 13: 9780195098709
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Seller: Kennys Bookstore, Olney, MD, U.S.A.
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Condition: New. This work presents research which adds visual learning capabilities to computer vision systems. Using this recognition technology, the outcome is different adaptive recognition systems that can measure their own performance, learn from their experience and outperform conventional static designs. Editor(s): Ikeuchi, Katsuchi; Veloso, Manuela M.; Velosa, Manuela. Num Pages: 368 pages, halftone and line figures, tables. BIC Classification: UYQN; UYQV. Category: (P) Professional & Vocational; (UP) Postgraduate, Research & Scholarly; (UU) Undergraduate. Dimension: 263 x 185 x 22. Weight in Grams: 825. . 1997. Hardback. . . . . Books ship from the US and Ireland. Seller Inventory # V9780195098709