Human Face Recognition Using Third-Order Synthetic Neural Networks
Pandya Abhijit S. Uwechue Okechukwu A.
ISBN 10: 1461368324 ISBN 13: 9781461368328
Editore: Springer, 2012
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PRINT ON DEMAND pp. 144. Codice articolo 1897851702
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Human Face Recognition Using Third-Order Synthetic Neural Networks explores the viability of the application of High-order synthetic neural network technology to transformation-invariant recognition of complex visual patterns. High-order networks require little training data (hence, short training times) and have been used to perform transformation-invariant recognition of relatively simple visual patterns, achieving very high recognition rates. The successful results of these methods provided inspiration to address more practical problems which have grayscale as opposed to binary patterns (e.g., alphanumeric characters, aircraft silhouettes) and are also more complex in nature as opposed to purely edge-extracted images - human face recognition is such a problem.
Human Face Recognition Using Third-Order Synthetic Neural Networks serves as an excellent reference for researchers and professionals working on applying neural network technology to the recognition of complex visual patterns.
Contenuti: Preface. List of Illustrations. List of Tables. 1. Introduction. 2. Face Recognition. 3. Implementation of Invariances. 4. Simple Pattern Recognition. 5. Facial Pattern Recognition. 6. Network Training. 7. Conclusions and Contributions. 8. Future Work. Index.
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Titolo: Human Face Recognition Using Third-Order ...
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Data di pubblicazione: 2012
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Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Human Face Recognition Using Third-Order Synthetic Neural Networks explores the viability of the application of High-order synthetic neural network technology to transformation-invariant recognition of complex visual patterns. High-ord. Codice articolo 4194994
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Taschenbuch. Condizione: Neu. Human Face Recognition Using Third-Order Synthetic Neural Networks | Okechukwu A. Uwechue (u. a.) | Taschenbuch | xv | Englisch | 2012 | Springer | EAN 9781461368328 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu. Codice articolo 105720906
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Human Face Recognition Using Third-Order Synthetic Neural Networks (The Springer International Series in Engineering and Computer Science, 410)
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Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Human Face Recognition Using Third-Order Synthetic Neural Networks explores the viability of the application of High-order synthetic neural network technology to transformation-invariant recognition of complex visual patterns. High-order networks require little training data (hence, short training times) and have been used to perform transformation-invariant recognition of relatively simple visual patterns, achieving very high recognition rates. The successful results of these methods provided inspiration to address more practical problems which have grayscale as opposed to binary patterns (e.g., alphanumeric characters, aircraft silhouettes) and are also more complex in nature as opposed to purely edge-extracted images - human face recognition is such a problem. Human Face Recognition Using Third-Order Synthetic Neural Networks serves as an excellent reference for researchers and professionals working on applying neural network technology to the recognition of complex visual patterns. 144 pp. Englisch. Codice articolo 9781461368328
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Human Face Recognition Using Third-Order Synthetic Neural Networks
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Springer US, Springer New York Okt 2012, 2012
ISBN 10: 1461368324
ISBN 13: 9781461368328
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Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Human Face Recognition Using Third-Order Synthetic Neural Networks explores the viability of the application of High-order synthetic neural network technology to transformation-invariant recognition of complex visual patterns. High-order networks require little training data (hence, short training times) and have been used to perform transformation-invariant recognition of relatively simple visual patterns, achieving very high recognition rates. The successful results of these methods provided inspiration to address more practical problems which have grayscale as opposed to binary patterns (e.g., alphanumeric characters, aircraft silhouettes) and are also more complex in nature as opposed to purely edge-extracted images - human face recognition is such a problem.Human Face Recognition Using Third-Order Synthetic Neural Networks serves as an excellent reference for researchers and professionals working on applying neural network technology to the recognition of complex visual patterns.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 144 pp. Englisch. Codice articolo 9781461368328
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Taschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - Human Face Recognition Using Third-Order Synthetic Neural Networks explores the viability of the application of High-order synthetic neural network technology to transformation-invariant recognition of complex visual patterns. High-order networks require little training data (hence, short training times) and have been used to perform transformation-invariant recognition of relatively simple visual patterns, achieving very high recognition rates. The successful results of these methods provided inspiration to address more practical problems which have grayscale as opposed to binary patterns (e.g., alphanumeric characters, aircraft silhouettes) and are also more complex in nature as opposed to purely edge-extracted images - human face recognition is such a problem. Human Face Recognition Using Third-Order Synthetic Neural Networks serves as an excellent reference for researchers and professionals working on applying neural network technology to the recognition of complex visual patterns. Codice articolo 9781461368328
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Human Face Recognition Using Third-Order Synthetic Neural Networks (The Springer International Series in Engineering and Computer Science, 410)
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