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Sprache: Englisch
Verlag: Oxford University Press, Incorporated, 1997
ISBN 10: 0195098706 ISBN 13: 9780195098709
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Zustand: 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,
Sprache: Englisch
Verlag: Oxford University Press, USA, 1997
ISBN 10: 0195098706 ISBN 13: 9780195098709
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Zustand: 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.
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Sprache: Englisch
Verlag: Oxford University Press Inc, 1997
ISBN 10: 0195098706 ISBN 13: 9780195098709
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In den WarenkorbZustand: 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. . . . .
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Sprache: Englisch
Verlag: Oxford University Press Inc, US, 1997
ISBN 10: 0195098706 ISBN 13: 9780195098709
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In den WarenkorbHardback. Zustand: New. 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.
Sprache: Englisch
Verlag: Oxford University Press, USA, 1997
ISBN 10: 0195098706 ISBN 13: 9780195098709
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Sprache: Englisch
Verlag: Oxford University Press Inc, 1997
ISBN 10: 0195098706 ISBN 13: 9780195098709
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In den WarenkorbZustand: 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.
Sprache: Englisch
Verlag: Oxford University Press Inc, US, 1997
ISBN 10: 0195098706 ISBN 13: 9780195098709
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In den WarenkorbHardback. Zustand: New. 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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Verlag: Oxford University Press Inc, 1997
ISBN 10: 0195098706 ISBN 13: 9780195098709
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Sprache: Englisch
Verlag: Oxford University Press Inc, New York, 1997
ISBN 10: 0195098706 ISBN 13: 9780195098709
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In den WarenkorbHardcover. Zustand: new. Hardcover. 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 theirexperience 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 machinevision and machine learning. Symbolic Visual Learning, as presented in this book, consists of an area of research that tries to overcome fundamental constraints, enhancing recognition systems that can measure their own performance, learn from their experience, and outperform conventional static designs. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
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Buch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - 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.
Sprache: Englisch
Verlag: Oxford University Press OUP, 1997
ISBN 10: 0195098706 ISBN 13: 9780195098709
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Buch. Zustand: Neu. Symbolic Visual Learning | Katsushi Ikeuchi (u. a.) | Buch | Gebunden | Englisch | 1997 | Oxford University Press | EAN 9780195098709 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.
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Zustand: New. PRINT ON DEMAND pp. 364.