Table 7.
10-fold cross-validation accuracy of the DNN models initialized using random weights.
Model | GAN_aug1 (100 inst./class) (%) | GAN_aug2 (150 inst./class) (%) | GAN_aug3 (200 inst./class) (%) |
---|---|---|---|
VGG-16 | 91.9 | 92.6 | 93.4 |
VGG-19 | 92.6 | 93.1 | 93.5 |
ResNet-18 | 92.7 | 94.0 | 94.6 |
ResNet-50 | 93.8 | 94.5 | 94.9 |
DenseNet-121 | 95.0 | 95.6 | 95.7 |
DenseNet-169 | 95.3 | 95.4 | 95.8 |