Table 1. Experimental comparison results of average accuracy of different detection methods on the ground. The table lists the test results of two public data sets RSOD and NWPU VHR-10. Judging from the single type detection results, our model performed well. From the average accuracy it seems that our model is better than other models.
RSOD | AP1 | AP2 | AP3 | AP4 | | | | | | | mAP |
YOLOv5n | 97.8 | 98.2 | 83.3 | 47.1 | | | | | | | 81.6 |
YOLOv5s | 98.2 | 98.6 | 82.3 | 44.8 | | | | | | | 83.5 |
YOLOv3-Tiny | 96.3 | 96.3 | 76.8 | 65.9 | | | | | | | 83.9 |
AS-YOLOv5n | 98.2 | 97.5 | 86.8 | 57.2 | | | | | | | 84.9 |
The types in the ROSD data set include: AP1 (aircraft), AP2 (oiltank), AP3 (overpass), AP4 (playground).
The types in the NWPU VHR-10 data set include: AP1 (airplane), AP2 (ship), AP3 (storage tank), AP4(baseball diamond), AP5 (tennis court), AP6 (basketball court), AP7 (ground track field), AP8 (harbor), AP9 (bridge), AP10 (vehicle).