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Biometric Authentication: A Machine Learning Approach - Kung, Sun-Yuan; Mak, Man-Wai; Lin, Shang-Hung
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Biometric Authentication: A Machine Learning Approach - new book

2004, ISBN: 0137074832, Lieferbar binnen 4-6 Wochen Shipping costs:Versandkostenfrei innerhalb der BRD

ID: 9780137074839

Internationaler Buchtitel. In englischer Sprache. Verlag: Prentice Hall, 476 Seiten, L=231mm, B=175mm, H=23mm, Gew.=771gr, [GR: I-T2 - Supplementals & Ancillaries], Kartoniert/Broschiert, Klappentext: * A breakthrough approach to improving biometrics performance* Constructing robust information processing systems for face and voice recognition* Supporting high-performance data fusion in multimodal systems* Algorithms, implementation techniques, and application examples Machine learning: driving significant improvements in biometric performance As they improve, biometric authentication systems are becoming increasingly indispensable for protecting life and property. This book introduces powerful machine learning techniques that significantly improve biometric performance in a broad spectrum of application domains. Three leading researchers bridge the gap between research, design, and deployment, introducing key algorithms as well as practical implementation techniques. They demonstrate how to construct robust information processing systems for biometric authentication in both face and voice recognition systems, and to support data fusion in multimodal systems. Coverage includes: * How machine learning approaches differ from conventional template matching* Theoretical pillars of machine learning for complex pattern recognition and classification* Expectation-maximization (EM) algorithms and support vector machines (SVM)* Multi-layer learning models and back-propagation (BP) algorithms* Probabilistic decision-based neural networks (PDNNs) for face biometrics* Flexible structural frameworks for incorporating machine learning subsystems in biometric applications* Hierarchical mixture of experts and inter-class learning strategies based on class-based modular networks* Multi-cue data fusion techniques that integrate face and voice recognition* Application case studies * A breakthrough approach to improving biometrics performance* Constructing robust information processing systems for face and voice recognition* Supporting high-performance data fusion in multimodal systems* Algorithms, implementation techniques, and application examples Machine learning: driving significant improvements in biometric performance As they improve, biometric authentication systems are becoming increasingly indispensable for protecting life and property. This book introduces powerful machine learning techniques that significantly improve biometric performance in a broad spectrum of application domains. Three leading researchers bridge the gap between research, design, and deployment, introducing key algorithms as well as practical implementation techniques. They demonstrate how to construct robust information processing systems for biometric authentication in both face and voice recognition systems, and to support data fusion in multimodal systems. Coverage includes: * How machine learning approaches differ from conventional template matching* Theoretical pillars of machine learning for complex pattern recognition and classification* Expectation-maximization (EM) algorithms and support vector machines (SVM)* Multi-layer learning models and back-propagation (BP) algorithms* Probabilistic decision-based neural networks (PDNNs) for face biometrics* Flexible structural frameworks for incorporating machine learning subsystems in biometric applications* Hierarchical mixture of experts and inter-class learning strategies based on class-based modular networks* Multi-cue data fusion techniques that integrate face and voice recognition* Application case studies

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Biometric Authentication: A Machine Learning Approach - Kung, Sun-Yuan / Mak, Man-Wai / Lin, Shang-Hung
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A breakthrough approach to improving biometrics performance Constructing robust information processing systems for face and voice recognition Supporting high-performance data fusion in multimodal systems Algorithms, implementation techniques, and application examples Machine learning: driving significant improvements in biometric performance As they improve, biometric authentication systems are becoming increasingly indispensable for protecting life and property. This book introduces powerful machine learning techniques that significantly improve biometric performance in a broad spectrum of application domains. Three leading researchers bridge the gap between research, design, and deployment, introducing key algorithms as well as practical implementation techniques. They demonstrate how to construct robust information processing systems for biometric authentication in both face and voice recognition systems, and to support data fusion in multimodal systems. Coverage includes: How machine learning approaches differ from conventional template matching Theoretical pillars of machine learning for complex pattern recognition and classification Expectation-maximization (EM) algorithms and support vector machines (SVM) Multi-layer learning models and back-propagation (BP) algorithms Probabilistic decision-based neural networks (PDNNs) for face biometrics Flexible structural frameworks for incorporating machine learning subsystems in biometric applications Hierarchical mixture of experts and inter-class learning strategies based on class-based modular networks Multi-cue data fusion techniques that integrate face and voice recognition Application case studies Biometric Authentication: A Machine Learning Approach Kung, Sun-Yuan / Mak, Man-Wai / Lin, Shang-Hung, Prentice Hall

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Biometric Authentication: A Machine Learning Approach - Sun-Yuan Kung, Man-Wai Mak, Shang-Hung Lin
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Sun-Yuan Kung, Man-Wai Mak, Shang-Hung Lin:
Biometric Authentication: A Machine Learning Approach - Paperback

ISBN: 0137074832

Taschenbuch, [EAN: 9780137074839], Prentice Hall, Englisch, Englisch, Englisch, Prentice Hall, Book, Prentice Hall, Prentice Hall, 62991011, Computer & Internet, 63910011, Apple, 63716011, Betriebssysteme, 63260011, Certification Central, 63595011, Datenbanken, 377645011, Digitale Fotografie & Video, 63904011, Digitale Musik, 63647011, Grafikdesign, 63681011, Hardware, 63851011, Home Computing, 63336011, Informatik, 63462011, Microsoft, 377660011, Mobile & Wireless EDV, 63116011, Netzwerke, 63381011, Programmieren, 377670011, Projektmanagement, 377663011, Sicherheit & Verschlüsselung, 63160011, Software, 63549011, Spiel- & Strategieführer, 62992011, Webentwicklung, 63532011, Wirtschaft & Kultur, 54071011, Genres, 52044011, Englische & weitere fremdsprachige Bücher, 60518011, Prinzip der Elektrizität, 60516011, Elektrotechnik, 60448011, Ingenieurwesen & Technik, 60447011, Architektur, Technik & Ingenieurswesen, 54071011, Genres, 52044011, Englische & weitere fremdsprachige Bücher, 208623031, Taschenbuch, 208621031, Format (binding_browse-bin), 366250011, Refinements, 52044011, Englische & weitere fremdsprachige Bücher

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Biometric Authentication: A Machine Learning Approach - Sun-Yuan Kung, Man-Wai Mak, Shang-Hung Lin
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Sun-Yuan Kung, Man-Wai Mak, Shang-Hung Lin:
Biometric Authentication: A Machine Learning Approach - Paperback

ISBN: 0137074832

Taschenbuch, [EAN: 9780137074839], Prentice Hall, Englisch, Englisch, Englisch, Prentice Hall, Book, Prentice Hall, Prentice Hall, 62991011, Computer & Internet, 63910011, Apple, 63716011, Betriebssysteme, 63260011, Certification Central, 63595011, Datenbanken, 377645011, Digitale Fotografie & Video, 63904011, Digitale Musik, 63647011, Grafikdesign, 63681011, Hardware, 63851011, Home Computing, 63336011, Informatik, 63462011, Microsoft, 377660011, Mobile & Wireless EDV, 63116011, Netzwerke, 63381011, Programmieren, 377670011, Projektmanagement, 377663011, Sicherheit & Verschlüsselung, 63160011, Software, 63549011, Spiel- & Strategieführer, 62992011, Webentwicklung, 63532011, Wirtschaft & Kultur, 54071011, Genres, 52044011, Englische & weitere fremdsprachige Bücher, 60518011, Prinzip der Elektrizität, 60516011, Elektrotechnik, 60448011, Ingenieurwesen & Technik, 60447011, Architektur, Technik & Ingenieurswesen, 54071011, Genres, 52044011, Englische & weitere fremdsprachige Bücher, 208623031, Taschenbuch, 208621031, Format (binding_browse-bin), 366250011, Refinements, 52044011, Englische & weitere fremdsprachige Bücher

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Biometric Authentication - S.Y. Kung; M.W. Mak; S. H. Lin
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S.Y. Kung; M.W. Mak; S. H. Lin:
Biometric Authentication - Paperback

2004, ISBN: 9780137074839

ID: 12555631

Softcover, Buch, [PU: Prentice Hall]

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Details of the book
Biometric Authentication: A Machine Learning Approach

* A breakthrough approach to improving biometrics performance* Constructing robust information processing systems for face and voice recognition* Supporting high-performance data fusion in multimodal systems* Algorithms, implementation techniques, and application examples Machine learning: driving significant improvements in biometric performance As they improve, biometric authentication systems are becoming increasingly indispensable for protecting life and property. This book introduces powerful machine learning techniques that significantly improve biometric performance in a broad spectrum of application domains. Three leading researchers bridge the gap between research, design, and deployment, introducing key algorithms as well as practical implementation techniques. They demonstrate how to construct robust information processing systems for biometric authentication in both face and voice recognition systems, and to support data fusion in multimodal systems. Coverage includes: * How machine learning approaches differ from conventional template matching* Theoretical pillars of machine learning for complex pattern recognition and classification* Expectation-maximization (EM) algorithms and support vector machines (SVM)* Multi-layer learning models and back-propagation (BP) algorithms* Probabilistic decision-based neural networks (PDNNs) for face biometrics* Flexible structural frameworks for incorporating machine learning subsystems in biometric applications* Hierarchical mixture of experts and inter-class learning strategies based on class-based modular networks* Multi-cue data fusion techniques that integrate face and voice recognition* Application case studies

Details of the book - Biometric Authentication: A Machine Learning Approach


EAN (ISBN-13): 9780137074839
ISBN (ISBN-10): 0137074832
Paperback
Publishing year: 2004
Publisher: Prentice Hall
476 Pages
Weight: 0,771 kg
Language: eng/Englisch

Book in our database since 20.05.2008 17:08:16
Book found last time on 14.07.2017 20:32:55
ISBN/EAN: 0137074832

ISBN - alternate spelling:
0-13-707483-2, 978-0-13-707483-9


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