Human Face Recognition Using (25 results)

Hardcover. Ex-library with stamp and library-signature. GOOD condition, some traces of use. Ancien Exemplaire de bibliothèque avec signature et cachet. BON état, quelques traces d'usure. Ehem. Bibliotheksexemplar mit Signatur und Stempel. GUTER Zustand, ein paar Gebrauchsspuren. C 1039: (1997) 9780792399575 Sprache: Englisch Gewicht in Gramm: 550.

Condition: Gut. Zustand: Gut | Sprache: Englisch | Produktart: Bücher | 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.

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Hardback. Condition: New. 1997 ed. This text 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 (for example, 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. This text serves as a reference for researchers and professionals working on applying neural network technology to the recognition of complex visual patterns.

Condition: New. pp. 144.

Taschenbuch. Condition: Neu. Human Face Recognition Using Third-Order Synthetic Neural Networks | Okechukwu A Uwechue (u. a.) | Taschenbuch | Einband - flex.(Paperback) | Englisch | 2012 | Springer Us | EAN 9781461368328 | Verantwortliche Person für die EU: Springer Nature Customer Service Center GmbH, Europaplatz 3, 69115 Heidelberg, productsafety[at]springernature[dot]com | Anbieter: preigu.

Taschenbuch. Condition: 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.

Condition: New. 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.

Gebunden. Condition: New. 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.

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Hardback. Condition: New. 1997 ed. This text 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 (for example, 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. This text serves as a reference for researchers and professionals working on applying neural network technology to the recognition of complex visual patterns.

Buch. Condition: Neu. 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.

Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -A Biometric system is a pattern recognition system. It operates by acquiring Biometric data from an individual, extracting a feature set from the acquired data, and comparing this feature set against the template set in the database. A number of Biometric characteristics exist and are in use in various applications. Each Biometric has its strengths and weaknesses, and the choice depends on the application. The match between a specific Biometric with an application is determined depending upon the operational mode of the application and the properties of the Biometric characteristic. Research in automated face recognition has been conducted since the 1960s. The reliability of face recognition schemes still poses a great challenge to the scientific community. Face recognition has several advantages over other Biometric techniques. Face recognition is natural, non-intrusive and easy to use since it is based on images recorded by a distant camera and can be very effective even if the user is not aware of the existence of the face recognition system. The increased interest in automated face recognition systems have gained largely due to increasing public concerns for security. 140 pp. Englisch.

Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. A Biometric system is a pattern recognition system. It operates by acquiring Biometric data from an individual, extracting a feature set from the acquired data, and comparing this feature set against the template set in the database. A number of Biometric c.

Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -A Biometric system is a pattern recognition system. It operates by acquiring Biometric data from an individual, extracting a feature set from the acquired data, and comparing this feature set against the template set in the database. A number of Biometric characteristics exist and are in use in various applications. Each Biometric has its strengths and weaknesses, and the choice depends on the application. The match between a specific Biometric with an application is determined depending upon the operational mode of the application and the properties of the Biometric characteristic. Research in automated face recognition has been conducted since the 1960s. The reliability of face recognition schemes still poses a great challenge to the scientific community. Face recognition has several advantages over other Biometric techniques. Face recognition is natural, non-intrusive and easy to use since it is based on images recorded by a distant camera and can be very effective even if the user is not aware of the existence of the face recognition system. The increased interest in automated face recognition systems have gained largely due to increasing public concerns for security.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 140 pp. Englisch.

Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - A Biometric system is a pattern recognition system. It operates by acquiring Biometric data from an individual, extracting a feature set from the acquired data, and comparing this feature set against the template set in the database. A number of Biometric characteristics exist and are in use in various applications. Each Biometric has its strengths and weaknesses, and the choice depends on the application. The match between a specific Biometric with an application is determined depending upon the operational mode of the application and the properties of the Biometric characteristic. Research in automated face recognition has been conducted since the 1960s. The reliability of face recognition schemes still poses a great challenge to the scientific community. Face recognition has several advantages over other Biometric techniques. Face recognition is natural, non-intrusive and easy to use since it is based on images recorded by a distant camera and can be very effective even if the user is not aware of the existence of the face recognition system. The increased interest in automated face recognition systems have gained largely due to increasing public concerns for security.

Taschenbuch. Condition: 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.

Condition: New. Print on Demand pp. 144 52:B&W 6.14 x 9.21in or 234 x 156mm (Royal 8vo) Case Laminate on White w/Gloss Lam.

Condition: New. PRINT ON DEMAND pp. 144.