Research Article
[Retracted] A Novel Attention-Based Lightweight Network for Multiscale Object Detection in Underwater Images
Table 3
Comparison of AP values of different methods for objects of different sizes. The best results are marked in bold.
| Method | | | | | |
| Yolov5 | 40.07 | 68.31 | 75.38 | 62.34 | 43.64 | RON | 43.57 | 72.45 | 78.03 | 65.17 | 45.49 | RefineDet | 44.21 | 73.49 | 79.07 | 65.42 | 46.03 | STDN | 43.61 | 74.08 | 80.15 | 66.39 | 46.55 | SWIPENet | 45.82 | 75.63 | 81.43 | 68.21 | 48.08 | Faster R-CNN-AON | 46.23 | 77.26 | 81.59 | 69.00 | 49.20 | RFBNet | 42.48 | 72.52 | 77.24 | 64.38 | 44.61 | Ours | 48.73 | 76.90 | 83.41 | 69.84 | 49.94 |
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