Articles liés à Hierarchical Neural Networks for Image Interpretation
Synopsis
Human performance in visual perception by far exceeds the performance of contemporary computer vision systems. While humans are able to perceive their environment almost instantly and reliably under a wide range of conditions, computer vision systems work well only under controlled conditions in limited domains.
This book sets out to reproduce the robustness and speed of human perception by proposing a hierarchical neural network architecture for iterative image interpretation. The proposed architecture can be trained using unsupervised and supervised learning techniques.
Applications of the proposed architecture are illustrated using small networks. Furthermore, several larger networks were trained to perform various nontrivial computer vision tasks.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
- ÉditeurSpringer
- Date d'édition2008
- ISBN 10 3540407227
- ISBN 13 9783540407225
- ReliureBroché
- Langueanglais
- Nombre de pages240
- Coordonnées du fabricantnon disponible
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Hierarchical Neural Networks for Image Interpretation (Lecture Notes in Computer Science, 2766)
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Springer, 2003
ISBN 10 : 3540407227
ISBN 13 : 9783540407225
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Hierarchical Neural Networks for Image Interpretation: 2766 (Lecture Notes in Computer Science)
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Hierarchical Neural Networks for Image Interpretation: 2766 (Lecture Notes in Computer Science)
Edité par
Springer 00/n /13 J, 2003
ISBN 10 : 3540407227
ISBN 13 : 9783540407225
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Hierarchical Neural Networks for Image Interpretation
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Hierarchical neural networks for image interpretation.
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Springer, Berlin, 2003
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23 cm. original paperback. 224 pp. ills. references. index. "Lecture Notes in Computer Science". -(libr labels, library stamp, otherwise (very) good). 370g. N° de réf. du vendeur 71746
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Hierarchical Neural Networks for Image Interpretation
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Springer Berlin Heidelberg, 2003
ISBN 10 : 3540407227
ISBN 13 : 9783540407225
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Kartoniert / Broschiert. Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Includes supplementary material: sn.pub/extrasHuman performance in visual perception by far exceeds the performance of contemporary computer vision systems. While humans are able to perceive their environment almost instantly and reliably unde. N° de réf. du vendeur 4888915
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Hierarchical Neural Networks for Image Interpretation (Lecture Notes in Computer Science)
Edité par
Springer, 2003
ISBN 10 : 3540407227
ISBN 13 : 9783540407225
Ancien ou d'occasion
Paperback
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Paperback. Etat : Very Good. Ex-library paperback in very nice condition with the usual markings and attachments. N° de réf. du vendeur UTD14a2148
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Hierarchical Neural Networks for Image Interpretation
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Springer Berlin Heidelberg, 2003
ISBN 10 : 3540407227
ISBN 13 : 9783540407225
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Taschenbuch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - Human performance in visual perception by far exceeds the performance of contemporary computer vision systems. While humans are able to perceive their environment almost instantly and reliably under a wide range of conditions, computer vision systems work well only under controlled conditions in limited domains.This booksets out to reproduce the robustness and speed of human perception by proposing a hierarchical neural network architecture for iterative image interpretation. The proposed architecture can be trained using unsupervised and supervised learning techniques. Applications of the proposed architecture are illustrated using small networks. Furthermore, several larger networks were trained to perform various nontrivial computer vision tasks. N° de réf. du vendeur 9783540407225
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Hierarchical Neural Networks for Image Interpretation
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Springer Berlin Heidelberg Aug 2003, 2003
ISBN 10 : 3540407227
ISBN 13 : 9783540407225
Neuf
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Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Human performance in visual perception by far exceeds the performance of contemporary computer vision systems. While humans are able to perceive their environment almost instantly and reliably under a wide range of conditions, computer vision systems work well only under controlled conditions in limited domains.This booksets out to reproduce the robustness and speed of human perception by proposing a hierarchical neural network architecture for iterative image interpretation. The proposed architecture can be trained using unsupervised and supervised learning techniques. Applications of the proposed architecture are illustrated using small networks. Furthermore, several larger networks were trained to perform various nontrivial computer vision tasks. 240 pp. Englisch. N° de réf. du vendeur 9783540407225
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Hierarchical Neural Networks for Image Interpretation (Lecture Notes in Computer Science, 2766)
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