Name
Abstract | ||
|---|---|---|
•A novel approach COSLAQ for cross modal similarity learning with active queries is proposed.•Disagreement-based active query strategy explores the most valuable supervised information.•Uncertainty of similarity learning model is utilized to avoid querying outliers and noises. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1016/j.patcog.2017.05.011 | Pattern Recognition |
Keywords | Field | DocType |
Active learning,Cross modal similarity learning,Metric learning | Similarity learning,Modalities,Data mining,Semi-supervised learning,Closeness,Artificial intelligence,Decision boundary,Active learning,Pattern recognition,Similarity heuristic,Mathematics,Modal,Machine learning | Journal |
Volume | Issue | ISSN |
75 | C | 0031-3203 |
Citations | PageRank | References |
2 | 0.36 | 32 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Nengneng Gao | 1 | 2 | 0.36 |
| Sheng-Jun Huang | 2 | 475 | 27.21 |
| Yifan Yan | 3 | 6 | 1.07 |
| Songcan Chen | 4 | 4148 | 191.89 |