Research Article
FFA-YOLOv7: Improved YOLOv7 Based on Feature Fusion and Attention Mechanism for Wearing Violation Detection in Substation Construction Safety
Table 3
Comparison of performance among state-of-the-art object detection models.
| Model | P (%) | R (%) | mAP (%) | F1 (%) | Speed (ms) |
| YOLOv5-s | 94.62 | 95.32 | 96.45 | 94.93 | 8.6 | YOLOv5-m | 95.14 | 95.33 | 96.67 | 95.22 | 12.0 | YOLOv5-l | 95.18 | 96.02 | 96.71 | 95.53 | 14.0 | YOLOv7 | 95.76 | 95.92 | 97.64 | 95.84 | 8.8 | YOLOv7-x | 95.55 | 96.45 | 97.82 | 96.00 | 11.5 | FFA-YOLOv7 | 95.92 | 97.13 | 98.16 | 96.50 | 9.6 |
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