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Discriminative learning in biometric...

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Discriminative learning in biometrics[electronic resource] /

紀錄類型:	書目-電子資源 : Monograph/item
杜威分類號:	570.15195
書名/作者:	Discriminative learning in biometrics/ by 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.
標題:	Computer science.
標題:	Pattern perception.
標題:	Computer Science.
標題:	Biometrics.
標題:	Pattern Recognition.
ISBN:	9789811020568
ISBN:	9789811020551
內容註:	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.
摘要、提要註:	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.
電子資源:	http://dx.doi.org/10.1007/978-981-10-2056-8

Discriminative learning in biometrics[electronic resource] /
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

Standard No.: 10.1007/978-981-10-2056-8doiSubjects--Topical Terms:

337787
Biometry.

LC Class. No.: QH323.5

Dewey Class. No.: 570.15195

Discriminative learning in biometrics[electronic resource] /
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505 0 $a 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.
520 $a 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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