Name
Abstract | ||
|---|---|---|
In many computer vision applications, an object can be represented by multiple different views. Due to the heterogeneous gap triggered by the different views’ inconsistent distributions, it is challenging to exploit these multiview data for cross-view retrieval and classification. Motivated by the fact that both labeled and unlabeled data can enhance the relations among different views, this artic... |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1109/TCYB.2020.2984489 | IEEE Transactions on Cybernetics |
Keywords | DocType | Volume |
Correlation,Kernel,Interviews,Computer science,Learning systems,Cybernetics,Computer vision | Journal | 52 |
Issue | ISSN | Citations |
3 | 2168-2267 | 0 |
PageRank | References | Authors |
0.34 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xu Wang | 1 | 21 | 1.97 |
| Peng Hu | 2 | 71 | 9.06 |
| Pei Liu | 3 | 12 | 1.50 |
| Dezhong Peng | 4 | 285 | 27.92 |