Table 3.
The hardware, software, and hyperparameters configurations for the deep learning model
| Project | Content |
|---|---|
| CPU | Intel Xeon E5-2682v4 |
| RAM | 16 G |
| GPU | Nvidia Tesla P4 |
| Operating system | Ubuntu 16.04 LTS |
| Cuda | Cuda8.0 with Cudnn v6 |
| Data processing | Python2.7, OpenCV, LabelImg, etc. |
| Deep learning framework | TensorFlow |
| Deep learning algorithm | Faster RCNN ResNet101 |
| Num classes | 2 (Japonica rice grain and Indica rice grain) |
| Batch size | 1 |
| Initial learning rate | 0.0003 |
| Learning rate | 0.0003 |
| Iteration steps | 30,000 |
| Minimum confidence | 0.9 |