Table 1.
Validation performance of VGG variations. DA: Data augmentation, DP: Data pre-processing, WCE: Weighted Cross-Entropy. Bold values imply the best performance and the underlined values imply the models that are selected for experimenting in real test set
| Model architecture | Training strategy | Validation loss |
|---|---|---|
| VGG11 | Half-Split | 0.49 |
| VGG16 | Half-Split | 0.51 |
| VGG19 | Half-Split | 0.59 |
| VGG11 | 5-fold (DA, DP) | 0.52 |
| VGG16 | 5-fold (DA, DP) | 0.63 |
| VGG19 | 5-fold (DA, DP) | 0.72 |
| VGG11 | 5-fold | 0.24 |
| VGG16 | 5-fold | 0.30 |
| VGG19 | 5-fold | 0.31 |
| VGG11 | 5-fold (WCE) | 0.27 |
| VGG16 | 5-fold (WCE) | 0.39 |
| VGG19 | 5-fold (WCE) | 0.52 |