Table 3 Comparison of the accuracy of different object detection networks
From: YOLO POD: a fast and accurate multi-task model for dense Soybean Pod counting
Models | R2 | MAE | MAPE | RMSE |
|---|---|---|---|---|
Mask R-CNN | 0.824 | 16.0 | 29.6% | 25.0 |
Swin-S Mask R-CNN | 0.894 | 10.1 | 18.3% | 18.0 |
YOLO V4 | 0.914 | 11.5 | 23.1% | 17.5 |
YOLOV5-L | 0.921 | 11.1 | 17.8% | 14.0 |
YOLOX-L | 0.918 | 8.72 | 17.5% | 14.4 |
YOLO POD | 0.967 | 4.18 | 10.0% | 6.48 |