Name
Title | ||
|---|---|---|
Saliency prediction by Mahalanobis distance of topological feature on deep color components. |
Abstract | ||
|---|---|---|
•A novel saliency prediction method with optimal scheme of color components is proposed.•A light-weight deep model with CNN is presented to learn the optimal scheme of color components.•A new fusion method of topological feature is proposed via calculating Mahalanobis distance. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1016/j.jvcir.2019.02.026 | Journal of Visual Communication and Image Representation |
Keywords | Field | DocType |
Saliency,Deep color components,Topological feature,Covariance matrix,Mahalanobis distance | Adjacency list,Computer vision,Topology,Saliency map,Pattern recognition,Salience (neuroscience),Matrix (mathematics),Mahalanobis distance,Artificial intelligence,Mathematics,Covariance | Journal |
Volume | ISSN | Citations |
60 | 1047-3203 | 1 |
PageRank | References | Authors |
0.36 | 0 | 7 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jiazhong Chen | 1 | 33 | 9.85 |
| Qingqing Li | 2 | 90 | 8.58 |
| Ping Li | 3 | 3 | 1.06 |
| Yu Han | 4 | 1 | 0.36 |
| Lei Wu | 5 | 7 | 4.25 |
| Hefei Ling | 6 | 241 | 39.63 |
| Weimin Wu | 7 | 236 | 43.97 |