Table 1 Experimental key parameters.
From: A streamlined approach for intelligent ship object detection using EL-YOLO algorithm
Category | Parameters | Result |
|---|---|---|
Training parameters | Optimizer | SGD |
Batch size | 4 | |
Epochs | 200 | |
Pretrain | Closed | |
Learning rate | 0.01 | |
Input images size | 640 × 640 | |
Momentum | 0.937 | |
Weight_decay | 0.0005 | |
Warmup_epochs | 3.0 | |
Experimental environment parameters | CPU | i7-12700H |
GPU | NVIDIA GeForce RTX 3060 | |
GPU memory size | 6Â GB | |
Programming language | Python 3.9.0 | |
Operation system | Win 11 | |
Module platform | Pytorch1.13.0 + cuda11.6 |
