Table 4 Yolov8 with attention results comparison.
From: Optimized YOLOv8 framework for intelligent rockfall detection on mountain roads
Model | AP@0.5 | AP@0.75 | parameters | GFLOPs |
|---|---|---|---|---|
Yolov8 | 0.878 | 0.507 | 3,005,843 | 8.1 |
Yolov8 + setnet | 0.882 | 0.503 | 3,014,035 | 8.1 |
Yolov8 + cbam | 0.877 | 0.496 | 3,071,733 | 8.1 |
Yolov8 + cpca | 0.881 | 0.508 | 3,132,883 | 8.2 |
