Name
Title | ||
|---|---|---|
Score-level fusion using generalized extreme value distribution and DSmT, for multi-biometric systems. |
Abstract | ||
|---|---|---|
Human recognition in a multi-biometric system is performed by combining biometric clues from different sources (multiple sensors, units, algorithms, samples and modalities) at different levels (sensor, feature, score, rank and decision level). Low computational complexity and adequate data for fusion make the score-level fusion a preferable option over other levels of fusion. However, incompatibil... |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1049/iet-bmt.2017.0076 | IET Biometrics |
Keywords | Field | DocType |
biometrics (access control),computational complexity,face recognition,iris recognition,sensor fusion | Pattern recognition,Generalized extreme value distribution,Computer science,Fusion,Face Recognition Grand Challenge,NIST,Artificial intelligence,Biometrics,Iris flower data set,Score,Computational complexity theory | Journal |
Volume | Issue | ISSN |
7 | 5 | 2047-4938 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Renu Sharma | 1 | 0 | 2.37 |
| Sukhendu Das | 2 | 238 | 33.82 |
| Padmaja Joshi | 3 | 1 | 1.98 |