Hierarchical Neural Networks for Image Interpretation: 2766 (Lecture Notes in Computer Science)

Sven Behnke

ISBN 10: 3540407227 / ISBN 13: 9783540407225

Editore: Springer 00/n /13 J, 2003

Riguardo questo articolo

Shipped within 24 hours from our UK warehouse. Clean, undamaged book with no damage to pages and minimal wear to the cover. Spine still tight, in very good condition. Remember if you are not happy, you are covered by our 100% money back guarantee.

Codice articolo 6545-9783540407225

Dati bibliografici

• Titolo: Hierarchical Neural Networks for Image Interpretation: 2766 (Lecture Notes in Computer Science)
• Editore: Springer 00/n /13 J
• Data di pubblicazione: 2003
• Lingua: Inglese
• ISBN 10: 3540407227
• ISBN 13: 9783540407225
• Rilegatura: Paperback
• Condizione: Very Good

Descrizione articolo

Riassunto

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.

Recensione

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)