联合多尺度与注意力机制的遥感图像目标检测
|
|
张云佐,郭威,蔡昭权,李文博
|
Remote sensing image target detection combining multi-scale and attention mechanism
|
|
Yun-zuo ZHANG,Wei GUO,Zhao-quan CAI,Wen-bo LI
|
|
| 表 2 不同算法模型在DIOR测试集上的对比 |
| Tab.2 Comparison of different algorithm models on DIOR test set % |
|
| 算法模型 | mAP | AP | | C1/C11 | C2/C12 | C3/C13 | C4/C14 | C5/C15 | C6/C16 | C7/C17 | C8/C18 | C9/C19 | C10/C20 | | RetinaNet[22] | 65.7 | 53.7/74.2 | 77.3/50.7 | 69.0/59.6 | 81.3/71.2 | 44.1/69.3 | 72.3/44.8 | 62.5/81.3 | 76.2/54.2 | 66.0/45.1 | 77.7/83.4 | | PANet[23] | 66.1 | 60.2/73.4 | 72.0/45.3 | 70.6/56.9 | 80.5/71.7 | 43.6/70.4 | 72.3/62.0 | 61.4/80.9 | 72.1/57.0 | 66.7/47.2 | 72.0/84.5 | | CBD-E[24] | 67.8 | 54.2/79.5 | 77.0/47.5 | 71.5/59.3 | 87.1/69.1 | 44.6/69.7 | 75.4/64.3 | 63.5/84.5 | 76.2/59.4 | 65.3/44.7 | 79.3/83.1 | | YOLOv5s | 68.7 | 78.3/73.1 | 65/58.3 | 74.3/57.4 | 90.6/91.8 | 44.3/67.9 | 80.1/82.7 | 48.9/89.1 | 57.7/49.7 | 63.2/55.4 | 68.6/78.1 | | Ours | 71.6 | 85.8/75.7 | 74.2/59.9 | 78.9/58.6 | 89.8/89.7 | 46.1/71.9 | 77.8/78.7 | 60.5/89.5 | 65.1/55.4 | 65.3/56.4 | 75.6/78.1 |
|
|
|