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Adaptive Biometric Systems Recent Advances and Challenges /
This timely and 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 ta...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor Corporativo: | |
| Otros Autores: | , , |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Cham :
Springer International Publishing : Imprint: Springer,
2015.
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| Edición: | 1st ed. 2015. |
| Colección: | Advances in Computer Vision and Pattern Recognition,
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| Temas: | |
| Acceso en línea: | Texto Completo |
MARC
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| 245 | 1 | 0 | |a Adaptive Biometric Systems |h [electronic resource] : |b Recent Advances and Challenges / |c edited by Ajita Rattani, Fabio Roli, Eric Granger. |
| 250 | |a 1st ed. 2015. | ||
| 264 | 1 | |a Cham : |b Springer International Publishing : |b Imprint: Springer, |c 2015. | |
| 300 | |a X, 134 p. 44 illus., 24 illus. in color. |b online resource. | ||
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| 490 | 1 | |a Advances in Computer Vision and Pattern Recognition, |x 2191-6594 | |
| 520 | |a This timely and 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. Topics and features: Presents a thorough introduction to the concept of adaptive biometric systems, detailing their taxonomy, levels of adaptation, and open issues and challenges 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 This comprehensive text/reference will be of great interest to researchers and practitioners engaged in systems science, information security or biometrics. Postgraduate and final-year undergraduate students of computer engineering will also appreciate the coverage of intelligent and adaptive schemes for cutting-edge pattern recognition and signal processing in changing environments. | ||
| 650 | 0 | |a Biometric identification. | |
| 650 | 0 | |a Pattern recognition systems. | |
| 650 | 0 | |a Signal processing. | |
| 650 | 0 | |a Artificial intelligence. | |
| 650 | 1 | 4 | |a Biometrics. |
| 650 | 2 | 4 | |a Automated Pattern Recognition. |
| 650 | 2 | 4 | |a Signal, Speech and Image Processing . |
| 650 | 2 | 4 | |a Artificial Intelligence. |
| 700 | 1 | |a Rattani, Ajita. |e editor. |4 edt |4 http://id.loc.gov/vocabulary/relators/edt | |
| 700 | 1 | |a Roli, Fabio. |e editor. |4 edt |4 http://id.loc.gov/vocabulary/relators/edt | |
| 700 | 1 | |a Granger, Eric. |e editor. |0 (orcid)0000-0001-6116-7945 |1 https://orcid.org/0000-0001-6116-7945 |4 edt |4 http://id.loc.gov/vocabulary/relators/edt | |
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| 830 | 0 | |a Advances in Computer Vision and Pattern Recognition, |x 2191-6594 | |
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