Symbolic visual learning (24 Ergebnisse)

Hardcover. Zustand: Good. some shelfwear/edgewear but still NICE! - may have remainder mark or previous owner's name Standard-sized.

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.…

Hardcover. Zustand: New. HARDCOVER, BRAND NEW COPY, Perfect Shape, No Black Remainder Mark,Fast Shipping With Online Tracking, International Orders shipped Global Priority Air Mail, All orders handled with care and shipped promptly in secure packaging, we ship Mon-Sat and send shipment confirmation emails. Our customer service is friendly, we answer emails fast, accept returns and work hard to deliver 100% Customer Satisfaction.…

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Zustand: 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. . . . .…

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.…

Hardcover. Zustand: Like New. LIKE NEW. SHIPS FROM MULTIPLE LOCATIONS. book.

Zustand: New.

Zustand: 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.…

Zustand: New.

Zustand: As New. Unread book in perfect condition.

Zustand: New. In English.

Zustand: As New. Unread book in perfect condition.

Hardback. 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.…

Hardback. 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.…

Zustand: new. Questo è un articolo print on demand.

HRD. Zustand: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

HRD. Zustand: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

Zustand: New. Print on Demand pp. 364.

Hardcover. 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.…

Zustand: New. Print on Demand pp. 364 68:B&W 7 x 10 in or 254 x 178 mm Case Laminate on White w/Gloss Lam.

Zustand: New. PRINT ON DEMAND pp. 364.

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.

Hardback. Zustand: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days.