Table 1 Experimental environment and parameters.
From: A rapid and precise algorithm for maize leaf disease detection based on YOLO MSM
Experimental environment | Parameters |
|---|---|
Operating system | Windows 10 |
GPU | NVIDIA GeForce RTX4090 |
CPU | Intel Core i9-10900k with 3.7 GHz |
pytorch framework | 2.0.1 |
Python version | 3.9 |
CUDA | 11.8 |
Input image size | 640 × 640 |
Initial learning rate | 0.1 |
Final learning rate | 0.1 |
Hyper-parameter | 0.1 |
Weight decay | 0.0005 |
Momentum | 0.937 |
Confidence-threshold | 0.2 |
IoU-threshold | 0.2 |
Early stopping | 100 |
optimizer | SGD |
Epochs | 500 |
Batch size | 16 |
