Table 3 Number of parameters and obtained AUC for each architecture
From: CNNs for automatic glaucoma assessment using fundus images: an extensive validation
Model name | # parameters (in millions) | AUC |
|---|---|---|
VGG16 | 138 | 0.9632 (0.0149) |
VGG19 | 144 | 0.9686 (0.0158) |
InceptionV3 | 23 | 0.9653 (0.0135) |
ResNet50 | 25 | 0.9614 (0.0171) |
Xception | 22 | 0.9605 (0.0170) |