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03397nam a22005295i 4500 |
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978-3-319-24865-3 |
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DE-He213 |
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20151204152246.0 |
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cr nn 008mamaa |
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151022s2015 gw | s |||| 0|eng d |
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|a 9783319248653
|9 978-3-319-24865-3
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|a 10.1007/978-3-319-24865-3
|2 doi
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|2 bisacsh
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|a 570.15195
|2 23
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|a Adaptive Biometric Systems
|h [electronic resource] :
|b Recent Advances and Challenges /
|c edited by Ajita Rattani, Fabio Roli, Eric Granger.
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| 250 |
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|a 1st ed. 2015.
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| 264 |
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|a Cham :
|b Springer International Publishing :
|b Imprint: Springer,
|c 2015.
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| 300 |
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|a X, 134 p. 44 illus., 24 illus. in color.
|b online resource.
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| 336 |
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|a text
|b txt
|2 rdacontent
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|a computer
|b c
|2 rdamedia
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|a online resource
|b cr
|2 rdacarrier
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| 347 |
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|a text file
|b PDF
|2 rda
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| 490 |
1 |
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|a Advances in Computer Vision and Pattern Recognition,
|x 2191-6586
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| 520 |
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|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.
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| 650 |
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|a Computer science.
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| 650 |
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|a Artificial intelligence.
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| 650 |
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0 |
|a Pattern recognition.
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| 650 |
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|a Biometrics (Biology).
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| 650 |
1 |
4 |
|a Computer Science.
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| 650 |
2 |
4 |
|a Biometrics.
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| 650 |
2 |
4 |
|a Pattern Recognition.
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| 650 |
2 |
4 |
|a Signal, Image and Speech Processing.
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| 650 |
2 |
4 |
|a Artificial Intelligence (incl. Robotics).
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| 700 |
1 |
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|a Rattani, Ajita.
|e editor.
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| 700 |
1 |
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|a Roli, Fabio.
|e editor.
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| 700 |
1 |
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|a Granger, Eric.
|e editor.
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| 710 |
2 |
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|a SpringerLink (Online service)
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| 773 |
0 |
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|t Springer eBooks
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| 776 |
0 |
8 |
|i Printed edition:
|z 9783319248639
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| 830 |
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0 |
|a Advances in Computer Vision and Pattern Recognition,
|x 2191-6586
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| 856 |
4 |
0 |
|u http://dx.doi.org/10.1007/978-3-319-24865-3
|z Full Text via HEAL-Link
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| 912 |
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|a ZDB-2-SCS
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| 950 |
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|a Computer Science (Springer-11645)
|
