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Publicado por The MIT Press, 2010
ISBN 10: 026201453XISBN 13: 9780262014533
Librería: Bellwetherbooks, McKeesport, PA, Estados Unidos de America
Libro
Hardcover. Condición: As New. 1. LIKE NEW!!! Has a red or black remainder mark on bottom/exterior edge of pages.
Publicado por Springer, 2001
ISBN 10: 0792373480ISBN 13: 9780792373483
Librería: Ammareal, Morangis, Francia
Libro
Hardcover. Condición: Bon. Ancien livre de bibliothèque. Légères traces d'usure sur la couverture. Edition 2001. Ammareal reverse jusqu'à 15% du prix net de cet article à des organisations caritatives. ENGLISH DESCRIPTION Book Condition: Used, Good. Former library book. Slight signs of wear on the cover. Edition 2001. Ammareal gives back up to 15% of this item's net price to charity organizations.
Publicado por Springer, 2012
ISBN 10: 1461356539ISBN 13: 9781461356530
Librería: booksXpress, Bayonne, NJ, Estados Unidos de America
Libro
Soft Cover. Condición: new.
Publicado por Springer, 2001
ISBN 10: 0792373480ISBN 13: 9780792373483
Librería: booksXpress, Bayonne, NJ, Estados Unidos de America
Libro
Hardcover. Condición: new.
Publicado por Springer, 2012
ISBN 10: 1461356539ISBN 13: 9781461356530
Librería: Lucky's Textbooks, Dallas, TX, Estados Unidos de America
Libro
Condición: New.
Publicado por Springer, 2001
ISBN 10: 0792373480ISBN 13: 9780792373483
Librería: Lucky's Textbooks, Dallas, TX, Estados Unidos de America
Libro
Condición: New.
Publicado por Springer, 2012
ISBN 10: 1461356539ISBN 13: 9781461356530
Librería: Ria Christie Collections, Uxbridge, Reino Unido
Libro Impresión bajo demanda
Condición: New. PRINT ON DEMAND Book; New; Fast Shipping from the UK. No. book.
Publicado por Springer, 2001
ISBN 10: 0792373480ISBN 13: 9780792373483
Librería: Ria Christie Collections, Uxbridge, Reino Unido
Libro Impresión bajo demanda
Condición: New. PRINT ON DEMAND Book; New; Fast Shipping from the UK. No. book.
Publicado por Springer US Jun 2001, 2001
ISBN 10: 0792373480ISBN 13: 9780792373483
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
Libro Impresión bajo demanda
Buch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Face Image Analysis by Unsupervised Learning explores adaptive approaches to image analysis. It draws upon principles of unsupervised learning and information theory to adapt processing to the immediate task environment. In contrast to more traditional approaches to image analysis in which relevant structure is determined in advance and extracted using hand-engineered techniques, Face Image Analysis by Unsupervised Learning explores methods that have roots in biological vision and/or learn about the image structure directly from the image ensemble. Particular attention is paid to unsupervised learning techniques for encoding the statistical dependencies in the image ensemble. The first part of this volume reviews unsupervised learning, information theory, independent component analysis, and their relation to biological vision. Next, a face image representation using independent component analysis (ICA) is developed, which is an unsupervised learning technique based on optimal information transfer between neurons. The ICA representation is compared to a number of other face representations including eigenfaces and Gabor wavelets on tasks of identity recognition and expression analysis. Finally, methods for learning features that are robust to changes in viewpoint and lighting are presented. These studies provide evidence that encoding input dependencies through unsupervised learning is an effective strategy for face recognition. Face Image Analysis by Unsupervised Learning is suitable as a secondary text for a graduate-level course, and as a reference for researchers and practitioners in industry. 196 pp. Englisch.
Publicado por Springer US, 2001
ISBN 10: 0792373480ISBN 13: 9780792373483
Librería: moluna, Greven, Alemania
Libro Impresión bajo demanda
Gebunden. Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Face Image Analysis by Unsupervised Learning explores adaptive approaches to image analysis. It draws upon principles of unsupervised learning and information theory to adapt processing to the immediate task environment. In contrast to more trad.
Publicado por Springer US, 2012
ISBN 10: 1461356539ISBN 13: 9781461356530
Librería: moluna, Greven, Alemania
Libro Impresión bajo demanda
Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Face Image Analysis by Unsupervised Learning explores adaptive approaches to image analysis. It draws upon principles of unsupervised learning and information theory to adapt processing to the immediate task environment. In contrast to more trad.
Publicado por Springer US, 2001
ISBN 10: 0792373480ISBN 13: 9780792373483
Librería: AHA-BUCH GmbH, Einbeck, Alemania
Libro
Buch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - Face Image Analysis by Unsupervised Learning explores adaptive approaches to image analysis. It draws upon principles of unsupervised learning and information theory to adapt processing to the immediate task environment. In contrast to more traditional approaches to image analysis in which relevant structure is determined in advance and extracted using hand-engineered techniques, Face Image Analysis by Unsupervised Learning explores methods that have roots in biological vision and/or learn about the image structure directly from the image ensemble. Particular attention is paid to unsupervised learning techniques for encoding the statistical dependencies in the image ensemble. The first part of this volume reviews unsupervised learning, information theory, independent component analysis, and their relation to biological vision. Next, a face image representation using independent component analysis (ICA) is developed, which is an unsupervised learning technique based on optimal information transfer between neurons. The ICA representation is compared to a number of other face representations including eigenfaces and Gabor wavelets on tasks of identity recognition and expression analysis. Finally, methods for learning features that are robust to changes in viewpoint and lighting are presented. These studies provide evidence that encoding input dependencies through unsupervised learning is an effective strategy for face recognition. Face Image Analysis by Unsupervised Learning is suitable as a secondary text for a graduate-level course, and as a reference for researchers and practitioners in industry.
Publicado por Springer US, 2012
ISBN 10: 1461356539ISBN 13: 9781461356530
Librería: AHA-BUCH GmbH, Einbeck, Alemania
Libro
Taschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - Face Image Analysis by Unsupervised Learning explores adaptive approaches to image analysis. It draws upon principles of unsupervised learning and information theory to adapt processing to the immediate task environment. In contrast to more traditional approaches to image analysis in which relevant structure is determined in advance and extracted using hand-engineered techniques, Face Image Analysis by Unsupervised Learning explores methods that have roots in biological vision and/or learn about the image structure directly from the image ensemble. Particular attention is paid to unsupervised learning techniques for encoding the statistical dependencies in the image ensemble. The first part of this volume reviews unsupervised learning, information theory, independent component analysis, and their relation to biological vision. Next, a face image representation using independent component analysis (ICA) is developed, which is an unsupervised learning technique based on optimal information transfer between neurons. The ICA representation is compared to a number of other face representations including eigenfaces and Gabor wavelets on tasks of identity recognition and expression analysis. Finally, methods for learning features that are robust to changes in viewpoint and lighting are presented. These studies provide evidence that encoding input dependencies through unsupervised learning is an effective strategy for face recognition. Face Image Analysis by Unsupervised Learning is suitable as a secondary text for a graduate-level course, and as a reference for researchers and practitioners in industry.
Publicado por Springer US Okt 2012, 2012
ISBN 10: 1461356539ISBN 13: 9781461356530
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
Libro Impresión bajo demanda
Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Face Image Analysis by Unsupervised Learning explores adaptive approaches to image analysis. It draws upon principles of unsupervised learning and information theory to adapt processing to the immediate task environment. In contrast to more traditional approaches to image analysis in which relevant structure is determined in advance and extracted using hand-engineered techniques, Face Image Analysis by Unsupervised Learning explores methods that have roots in biological vision and/or learn about the image structure directly from the image ensemble. Particular attention is paid to unsupervised learning techniques for encoding the statistical dependencies in the image ensemble. The first part of this volume reviews unsupervised learning, information theory, independent component analysis, and their relation to biological vision. Next, a face image representation using independent component analysis (ICA) is developed, which is an unsupervised learning technique based on optimal information transfer between neurons. The ICA representation is compared to a number of other face representations including eigenfaces and Gabor wavelets on tasks of identity recognition and expression analysis. Finally, methods for learning features that are robust to changes in viewpoint and lighting are presented. These studies provide evidence that encoding input dependencies through unsupervised learning is an effective strategy for face recognition. Face Image Analysis by Unsupervised Learning is suitable as a secondary text for a graduate-level course, and as a reference for researchers and practitioners in industry. 192 pp. Englisch.
Publicado por Springer, 2012
ISBN 10: 1461356539ISBN 13: 9781461356530
Librería: dsmbooks, Liverpool, Reino Unido
Libro
Paperback. Condición: Like New. Like New. book.
Publicado por Springer, 2001
ISBN 10: 0792373480ISBN 13: 9780792373483
Librería: Mispah books, Redhill, SURRE, Reino Unido
Libro
Hardcover. Condición: Like New. Like New. book.