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Record Nr. |
UNISA996465961503316 |
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Autore |
Behnke Sven |
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Titolo |
Hierarchical Neural Networks for Image Interpretation [[electronic resource] /] / by Sven Behnke |
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Pubbl/distr/stampa |
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Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2003 |
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ISBN |
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Edizione |
[1st ed. 2003.] |
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Descrizione fisica |
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1 online resource (XIII, 227 p.) |
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Collana |
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Lecture Notes in Computer Science, , 0302-9743 ; ; 2766 |
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Disciplina |
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Soggetti |
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Computers |
Neurosciences |
Algorithms |
Artificial intelligence |
Optical data processing |
Pattern recognition |
Computation by Abstract Devices |
Algorithm Analysis and Problem Complexity |
Artificial Intelligence |
Image Processing and Computer Vision |
Pattern Recognition |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Bibliographic Level Mode of Issuance: Monograph |
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Nota di bibliografia |
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Includes bibliographical references and index. |
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Nota di contenuto |
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I. Theory -- Neurobiological Background -- Related Work -- Neural Abstraction Pyramid Architecture -- Unsupervised Learning -- Supervised Learning -- II. Applications -- Recognition of Meter Values -- Binarization of Matrix Codes -- Learning Iterative Image Reconstruction -- Face Localization -- Summary and Conclusions. |
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Sommario/riassunto |
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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 |
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