Table 3 Comparison of results of different algorithms.
From: Development of a deep learning-based foreign object detection algorithm for coal mine conveyor belts
Model name | Params/M | FLOPs/G | Model/MB | mAP@0.5/% | mAP@[0.50:0.95]/% | mAP@0.75/% | Precision/% | Recall/% |
|---|---|---|---|---|---|---|---|---|
YOLOv5n | 2.1 | 5.8 | 4.7 | 92.2 | 75.2 | 80.7 | 98.2 | 97 |
YOLOv6n | 4.1 | 11.5 | 8.6 | 92.2 | 74.8 | 81.2 | 95.7 | 96 |
YOLOv8n | 2.6 | 6.8 | 5.6 | 92.6 | 75.6 | 82.3 | 95.4 | 96 |
YOLOv9t | 1.7 | 6.4 | 4.1 | 92.7 | 76.8 | 83.7 | 97.3 | 96 |
YOLOv10n | 2.6 | 8.2 | 5.8 | 92.3 | 75.7 | 81.5 | 98.8 | 96 |
YOLOv11n | 2.5 | 6.3 | 5.5 | 93 | 76.8 | 82.7 | 96.6 | 96 |
YOLOv12n | 2.5 | 5.8 | 5.2 | 942 | 77.5 | 84.1 | 97.2 | 98 |
YOLOv13n | 2.4 | 6.1 | 5.1 | 93 | 76.9 | 83.3 | 96.8 | 97 |
YOLOv11-ASCL | 1.8 | 4.2 | 3.9 | 94.5 | 76.9 | 84.2 | 97.8 | 98 |
