Name
Abstract | ||
|---|---|---|
•A method for extracting short descriptors from lengthy descriptors is developed.•The dimension reduction results are strengthened by an attraction/repulsion model.•A deep residual network is trained for generating the short descriptors.•The short descriptors improve the retrieval speed greatly. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1016/j.cag.2019.04.002 | Computers & Graphics |
Keywords | Field | DocType |
Shape retrieval,Shape descriptor,Dimensionality reduction,ResNet | Residual,Computer vision,Architecture,Dimensionality reduction,Pattern recognition,Computer science,Artificial intelligence,Deep learning,Dimensional reduction,Residual neural network,Real number | Journal |
Volume | ISSN | Citations |
81 | 0097-8493 | 1 |
PageRank | References | Authors |
0.35 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| zihao wang | 1 | 76 | 15.10 |
| Hongwei Lin | 2 | 381 | 38.62 |
| xiaofeng yu | 3 | 5 | 1.16 |
| Yusuf Fatihu Hamza | 4 | 1 | 0.35 |