Name
Title | ||
|---|---|---|
Gender Attribute Mining With Hand-Dorsa Vein Image Based On Unsupervised Sparse Feature Learning |
Abstract | ||
|---|---|---|
Gender classification with hand-dorsa vein information, a new soft biometric trait, is solved with the proposed unsupervised sparse feature learning model, state-of-the-art accuracy demonstrates the effectiveness of the proposed model. Besides, we also argue that the proposed data reconstruction model is also applicable to age estimation when comprehensive database differing in age is accessible. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1587/transinf.2017EDL8098 | IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS |
Keywords | Field | DocType |
gender recognition, unsupervised sparse feature learning, data reconstruction | Computer vision,Pattern recognition,Computer science,Image based,Artificial intelligence,Feature learning | Journal |
Volume | Issue | ISSN |
E101D | 1 | 1745-1361 |
Citations | PageRank | References |
0 | 0.34 | 8 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jun Wang | 1 | 9228 | 736.82 |
| Guoqing Wang | 2 | 75 | 17.84 |
| Zaiyu Pan | 3 | 2 | 2.75 |