Research Article
[Retracted] Fast Recognition Method for Multiple Apple Targets in Complex Occlusion Environment Based on Improved YOLOv5
Table 3
Evaluation results of 5 algorithms under different occlusions.
| Method | Precision/% | Recall/% | /% | Average image recognition time/s |
| Hog + SVM | 73.50 | 75.34 | 74.4 | 0.296 | Faster RCNN | 81.06 | 80.32 | 80.69 | 0.255 | YOLOv6 | 93.76 | 90.6 | 92.15 | 0.024 | Baseline YOLOv5 | 90.23 | 88.76 | 89.49 | 0.036 | Improved YOLOv5 | 94.64 | 92.89 | 93.76 | 0.026 |
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