Research Article
An Evaluation of Deep Learning Methods for Small Object Detection
Table 2
The parameters of models.
| Method | Momentum | Decay | Gamma | Learning_rate | Batch_size | Training_days | Stepsize |
| YOLOv2 [16] | 0.9 | 0.0005 | | 0.001 | 8 | 5 | 25000 | YOLOv3 | 0.9 | 0.0005 | | 0.001 | 32 | 3–4 | 25000 | SSD300 [16] | 0.9 | 0.0005 | 0.1 | 0.000004 | 12 | 9 | 40000, 80000 | SSD512 [16] | 0.9 | 0.0005 | 0.1 | 0.000004 | 12 | 12 | 100000, 120000 | RetinaNet | 0.9 | 0.0005 | 0.1 | 0.001 | 64 | 4->12 h | 25000, 35000 | Fast RCNN | 0.9 | 0.0005 | 0.1 | 0.001 | 64 | 4->12 h | 25000, 35000 | Faster RCNN | 0.9 | 0.0005 | 0.1 | 0.001 | 64 | 4->12 h | 25000, 35000 |
|
|