Research Article
Yolov4 High-Speed Train Wheelset Tread Defect Detection System Based on Multiscale Feature Fusion
Table 2
Detection results on WT-DET.
| Method | Recall (%) | Precision (%) | mAP (%) | Fps | F1 |
| SSD [19] | 69.70 | 97.87 | 77.39 | 47.11 | 0.81 | CenterNet [37] | 65.15 | 95.56 | 84.82 | 63.95 | 0.77 | Faster R-CNN [16] | 72.73 | 48.48 | 73.36 | 2.05 | 0.58 | RetinaNet [20] | 75.76 | 90.91 | 82.67 | 45.28 | 0.83 | RFB Net [38] | 74.24 | 89.09 | 78.38 | 39.96 | 0.81 | M2Det [39] | 75.76 | 98.04 | 84.57 | 39.69 | 0.85 | Our method | 78.79 | 94.55 | 86.25 | 37.05 | 0.86 |
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