Name
Abstract | ||
|---|---|---|
•The first deep learning method for heterogeneous iris verification.•The filter pairs are automatically learned rather than hand-crafted.•The filter pairs are source-specific for heterogeneous iris verification.•The EER (Equal Error Rate) of heterogeneous iris verification is reduced by 90%. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1016/j.patrec.2015.09.016 | Pattern Recognition Letters |
Keywords | Field | DocType |
Biometrics,Iris verification,Convolutional neural networks,Deep learning,Iris recognition | Iris recognition,Pairwise comparison,Computer vision,Pattern recognition,Computer science,Convolutional neural network,Filter bank,Word error rate,Feature extraction,Artificial intelligence,Deep learning,Biometrics | Journal |
Volume | ISSN | Citations |
82 | 0167-8655 | 28 |
PageRank | References | Authors |
0.77 | 19 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| nianfeng liu | 1 | 28 | 0.77 |
| Man Zhang | 2 | 113 | 15.27 |
| Haiqing Li | 3 | 77 | 7.57 |
| Zhenan Sun | 4 | 2379 | 139.49 |
| Tieniu Tan | 5 | 11681 | 744.35 |