|
|
|
|
| LEADER |
03150nam a22005055i 4500 |
| 001 |
978-981-10-2056-8 |
| 003 |
DE-He213 |
| 005 |
20210619000956.0 |
| 007 |
cr nn 008mamaa |
| 008 |
161026s2016 si | s |||| 0|eng d |
| 020 |
|
|
|a 9789811020568
|9 978-981-10-2056-8
|
| 024 |
7 |
|
|a 10.1007/978-981-10-2056-8
|2 doi
|
| 050 |
|
4 |
|a QH323.5
|
| 072 |
|
7 |
|a UYQP
|2 bicssc
|
| 072 |
|
7 |
|a COM016000
|2 bisacsh
|
| 072 |
|
7 |
|a UYQP
|2 thema
|
| 072 |
|
7 |
|a UYQV
|2 thema
|
| 082 |
0 |
4 |
|a 570.15195
|2 23
|
| 100 |
1 |
|
|a Zhang, David.
|e author.
|4 aut
|4 http://id.loc.gov/vocabulary/relators/aut
|
| 245 |
1 |
0 |
|a Discriminative Learning in Biometrics
|h [electronic resource] /
|c by David Zhang, Yong Xu, Wangmeng Zuo.
|
| 250 |
|
|
|a 1st ed. 2016.
|
| 264 |
|
1 |
|a Singapore :
|b Springer Singapore :
|b Imprint: Springer,
|c 2016.
|
| 300 |
|
|
|a XIII, 266 p. 110 illus., 73 illus. in color.
|b online resource.
|
| 336 |
|
|
|a text
|b txt
|2 rdacontent
|
| 337 |
|
|
|a computer
|b c
|2 rdamedia
|
| 338 |
|
|
|a online resource
|b cr
|2 rdacarrier
|
| 347 |
|
|
|a text file
|b PDF
|2 rda
|
| 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. .
|
| 650 |
|
0 |
|a Biometrics (Biology).
|
| 650 |
|
0 |
|a Pattern recognition.
|
| 650 |
1 |
4 |
|a Biometrics.
|0 https://scigraph.springernature.com/ontologies/product-market-codes/I22040
|
| 650 |
2 |
4 |
|a Pattern Recognition.
|0 https://scigraph.springernature.com/ontologies/product-market-codes/I2203X
|
| 700 |
1 |
|
|a Xu, Yong.
|e author.
|4 aut
|4 http://id.loc.gov/vocabulary/relators/aut
|
| 700 |
1 |
|
|a Zuo, Wangmeng.
|e author.
|4 aut
|4 http://id.loc.gov/vocabulary/relators/aut
|
| 710 |
2 |
|
|a SpringerLink (Online service)
|
| 773 |
0 |
|
|t Springer Nature eBook
|
| 776 |
0 |
8 |
|i Printed edition:
|z 9789811020551
|
| 776 |
0 |
8 |
|i Printed edition:
|z 9789811020575
|
| 776 |
0 |
8 |
|i Printed edition:
|z 9789811095153
|
| 856 |
4 |
0 |
|u https://doi.org/10.1007/978-981-10-2056-8
|
| 912 |
|
|
|a ZDB-2-SCS
|
| 912 |
|
|
|a ZDB-2-SXCS
|
| 950 |
|
|
|a Computer Science (SpringerNature-11645)
|
| 950 |
|
|
|a Computer Science (R0) (SpringerNature-43710)
|
