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Discriminative learning in biometrics
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Discriminative learning in biometrics
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Discriminative learning in biometricsby David Zhang, Yong Xu, Wangmeng Zuo.
作者:
Zhang, David.
其他作者:
Xu, Yong.
出版者:
Singapore :Springer Singapore :2016.
面頁冊數:
xiii, 266 p. :ill., digital ;24 cm.
Contained By:
Springer eBooks
標題:
Biometry.
電子資源:
http://dx.doi.org/10.1007/978-981-10-2056-8
ISBN:
9789811020568$q(electronic bk.)
Discriminative learning in biometrics
Zhang, David.
Discriminative learning in biometrics
[electronic resource] /by David Zhang, Yong Xu, Wangmeng Zuo. - Singapore :Springer Singapore :2016. - xiii, 266 p. :ill., digital ;24 cm.
1. Discriminative Learning in Biometrics -- 2. Metric Learning with Biometric Applications -- 3. Sparse Representation-based Classification for Biometric Recognition -- 4. Discriminative Features for Palmprint Authentication -- 5. Orientation Features and Distance Measure of Palmprint Authentication -- 6. Multifeature Palmprint Authentication -- 7. Discriminative Learning via Encouraging Virtual Face Images -- 8. Sparse Representation-based Methods for Face Recognition -- 9. Fusion Methodologies of Multiple Traits -- 10. Discussions and Future Work.
This monograph describes the latest advances in discriminative learning methods for biometric recognition. Specifically, it focuses on three representative categories of methods: sparse representation-based classification, metric learning, and discriminative feature representation, together with their applications in palmprint authentication, face recognition and multi-biometrics. The ideas, algorithms, experimental evaluation and underlying rationales are also provided for a better understanding of these methods. Lastly, it discusses several promising research directions in the field of discriminative biometric recognition.
ISBN: 9789811020568$q(electronic bk.)
Standard No.: 10.1007/978-981-10-2056-8doiSubjects--Topical Terms:
182039
Biometry.
LC Class. No.: QH323.5
Dewey Class. No.: 570.15195
Discriminative learning in biometrics
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This monograph describes the latest advances in discriminative learning methods for biometric recognition. Specifically, it focuses on three representative categories of methods: sparse representation-based classification, metric learning, and discriminative feature representation, together with their applications in palmprint authentication, face recognition and multi-biometrics. The ideas, algorithms, experimental evaluation and underlying rationales are also provided for a better understanding of these methods. Lastly, it discusses several promising research directions in the field of discriminative biometric recognition.
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