Adaptive Biometric Systems : Recent Advances and Challenges
Language: English
Published by Palgrave Macmillan, 2015
Series: Book 50 of 86 - Advances in Computer Vision and Pattern Recognition
- Hardcover
- Used
Seller: Buchpark, Trebbin, GermanyBuchpark
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Add to basketItem description from seller
Zustand: Sehr gut | Sprache: Englisch | Produktart: Bücher | This interdisciplinary volume presents a detailed overview of the latest advances and challenges remaining in the field of adaptive biometric systems. A broad range of techniques are provided from an international selection of pre-eminent authorities, collected together under a unified taxonomy and designed to be applicable to any pattern recognition system. Features: presents a thorough introduction to the concept of adaptive biometric systems; reviews systems for adaptive face recognition that perform self-updating of facial models using operational (unlabeled) data; describes a novel semi-supervised training strategy known as fusion-based co-training; examines the characterization and recognition of human gestures in videos; discusses a selection of learning techniques that can be applied to build an adaptive biometric system; investigates procedures for handling temporal variance in facial biometrics due to aging; proposes a score-level fusion scheme for an adaptive multimodal biometric system. …
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- Title
- Adaptive Biometric Systems : Recent Advances and Challenges
- Author
- Unbekannt
- Publisher
- Palgrave Macmillan
- Publication year
- 2015
- Condition
- Sehr gut
- Binding
- Hardcover
- Language
- English
- ISBN 10
- 3319248634
- ISBN 13
- 9783319248639
- Series
- Book 50 of 86: Advances in Computer Vision and Pattern Recognition
- Seller catalogs
- Bücher
This interdisciplinary volume presents a detailed overview of the latest advances and challenges remaining in the field of adaptive biometric systems. A broad range of techniques are provided from an international selection of pre-eminent authorities, collected together under a unified taxonomy and designed to be applicable to any pattern recognition system. Features: presents a thorough introduction to the concept of adaptive biometric systems; reviews systems for adaptive face recognition that perform self-updating of facial models using operational (unlabeled) data; describes a novel semi-supervised training strategy known as fusion-based co-training; examines the characterization and recognition of human gestures in videos; discusses a selection of learning techniques that can be applied to build an adaptive biometric system; investigates procedures for handling temporal variance in facial biometrics due to aging; proposes a score-level fusion scheme for an adaptive multimodal biometric system.
"Synopsis" may belong to another edition of this title.
About the Author
Dr. Ajita Rattani is a post-doctoral fellow in the Integrated Pattern Recognition and Biometrics (i-PRoBe) lab at Michigan State University, East Lansing, MI, USA. Dr. Fabio Roli is a professor of computer engineering and the Director of the Pattern Recognition and Applications (PRA) lab at the University of Cagliari, Italy. Dr. Eric Granger is a professor in the Department of Automated Manufacturing Engineering and the Director of the Laboratory for Imagery, Vision and Artificial Intelligence at the École de technologie supérieure (ÉTS), Montréal, QC, Canada.
"About the title" may belong to another edition of this title.
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