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Hierarchical Neural Networks for Image Interpretation: 2766 (Lecture Notes in Computer Science) - Softcover
Inhaltsangabe
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.
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Críticas
From the reviews:
"This booklet is the reprint of a thesis. It addresses image interpretation using a neural network architecture mimicking the human visual system. ... The exposition is divided in two parts, namely theory and applications. ... In short this thesis is very interesting, well written and easy to read." (Jean Th. Lapresté, Zentralblatt MATH, Vol. 1041 (16), 2004)
Reseña del editor
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.
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- VerlagSpringer
- Erscheinungsdatum2008
- ISBN 10 3540407227
- ISBN 13 9783540407225
- EinbandTapa blanda
- SpracheEnglisch
- Anzahl der Seiten240
- Kontakt zum HerstellerNicht verfügbar
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Hierarchical Neural Networks for Image Interpretation (Lecture Notes in Computer Science, 2766)
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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.
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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. Bestandsnummer des Verkäufers 71746
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Hierarchical Neural Networks for Image Interpretation
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Springer-Verlag Berlin and Heidelberg GmbH & Co. K, 2003
ISBN 10: 3540407227
ISBN 13: 9783540407225
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Hierarchical Neural Networks for Image Interpretation
Verlag:
Springer Berlin Heidelberg, 2003
ISBN 10: 3540407227
ISBN 13: 9783540407225
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Kartoniert / Broschiert. Zustand: 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. Bestandsnummer des Verkäufers 4888915
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Hierarchical Neural Networks for Image Interpretation
ISBN 10: 3540407227
ISBN 13: 9783540407225
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Taschenbuch. Zustand: Neu. 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 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.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 240 pp. Englisch. Bestandsnummer des Verkäufers 9783540407225
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Taschenbuch. Zustand: 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. Bestandsnummer des Verkäufers 9783540407225
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Hierarchical Neural Networks for Image Interpretation
Verlag:
Springer Berlin Heidelberg Aug 2003, 2003
ISBN 10: 3540407227
ISBN 13: 9783540407225
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Taschenbuch. Zustand: 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. Bestandsnummer des Verkäufers 9783540407225
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Hierarchical Neural Networks for Image Interpretation (Lecture Notes in Computer Science, 2766)
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