Name
Abstract | ||
|---|---|---|
Object detection in aerial images is important for a wide range of applications. The most challenging dilemma in this task is the arbitrary orientation of objects, and many deep-learning-based methods are proposed to address this issue. In previous works on oriented object detection, the regression-based method for object localization has limited performance due to the shortage of spatial informat... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/TGRS.2020.3020165 | IEEE Transactions on Geoscience and Remote Sensing |
Keywords | DocType | Volume |
Object detection,Detectors,Task analysis,Feature extraction,Predictive models,Object recognition,Quantization (signal) | Journal | 59 |
Issue | ISSN | Citations |
5 | 0196-2892 | 0 |
PageRank | References | Authors |
0.34 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Kun Fu | 1 | 414 | 57.81 |
| Zhonghan Chang | 2 | 2 | 1.38 |
| Yue Zhang | 3 | 184 | 53.93 |
| Xian Sun | 4 | 325 | 40.42 |