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Published by Elsevier Science & Technology, 2022
ISBN 10: 0323852092 ISBN 13: 9780323852098
Language: English
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Taschenbuch. Condition: Neu. Machine Learning for Biometrics | Concepts, Algorithms and Applications | Partha Pratim Sarangi (u. a.) | Taschenbuch | Einband - flex.(Paperback) | Englisch | 2022 | Academic Press | EAN 9780323852098 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.
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Published by Elsevier Science & Technology|Academic Press, 2022
ISBN 10: 0323852092 ISBN 13: 9780323852098
Language: English
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Machine Learning for Biometrics: Concepts, Algorithms and Applications highlights the fundamental concepts of machine learning, processing and analyzing data from biometrics and provides a review of intelligent and cognitive learning tools which c.
Published by Elsevier Science & Technology, 2022
ISBN 10: 0323852092 ISBN 13: 9780323852098
Language: English
Seller: THE SAINT BOOKSTORE, Southport, United Kingdom
Paperback / softback. Condition: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days 430.
Published by Elsevier Science & Technology, Academic Press, 2022
ISBN 10: 0323852092 ISBN 13: 9780323852098
Language: English
Seller: AHA-BUCH GmbH, Einbeck, Germany
Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Machine Learning for Biometrics: Concepts, Algorithms and Applications highlights the fundamental concepts of machine learning, processing and analyzing data from biometrics and provides a review of intelligent and cognitive learning tools which can be adopted in this direction. Each chapter of the volume is supported by real-life case studies, illustrative examples and video demonstrations. The book elucidates various biometric concepts, algorithms and applications with machine intelligence solutions, providing guidance on best practices for new technologies such as e-health solutions, Data science, Cloud computing, and Internet of Things, etc. In each section, different machine learning concepts and algorithms are used, such as different object detection techniques, image enhancement techniques, both global and local feature extraction techniques, and classifiers those are commonly used data science techniques. These biometrics techniques can be used as tools in Cloud computing, Mobile computing, IOT based applications, and e-health care systems for secure login, device access control, personal recognition and surveillance.