Table 3 Comparison of test results of different detection algorithms
From: GrainNet: efficient detection and counting of wheat grains based on an improved YOLOv7 modeling
Models | P (%) | R (%) | F1 | mAP@0.5 (%) |
|---|---|---|---|---|
Faster-RCNN | 79.64 | 67.96 | 0.733 | 71.26 |
YOLOv5 | 95.48 | 84.84 | 0.897 | 90.70 |
YOLOv7 | 96.04 | 88.49 | 0.921 | 91.69 |
YOLOv8 | 93.80 | 88.86 | 0.910 | 92.86 |
GrainNet | 97.32 | 92.05 | 0.946 | 93.15 |