Hidden Bibliographic Details
| ISBN: | 9783540451693
3540451692
3540407227
9783540407225
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| Digital file characteristics: | text file PDF
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| Notes: | Includes bibliographical references and index.
English.
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| Summary: | 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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| Other form: | Print version:Behnke, Sven. Hierarchical neural networks for image interpretation
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| Standard no.: | 10.1007/b11963
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