Table 11.
Average-wise performance comparison of all the models
| Model NAME | All experiments average F1 | All experiments average AUC | All experiments average accuracy |
|---|---|---|---|
| VGG-16 | 0.920733 | 0.888575 | 0.914426 |
| VGG-19 | 0.915139 | 0.903742 | 0.921005 |
| MobileNet | 0.911087 | 0.919878 | 0.925677 |
| InceptionResNetV2 | 0.904686 | 0.913151 | 0.920659 |
| InceptionV3 | 0.896025 | 0.885667 | 0.882325 |
| ResNet-101 | 0.899679 | 0.900224 | 0.899411 |
| ResNet50V2 | 0.880875 | 0.910234 | 0.919958 |
| ResNet-101V2 | 0.8971 | 0.9036 | 0.8989 |
| Xception | 0.917826 | 0.902268 | 0.91461 |
| SqueezeNet | 0.521689 | 0.530245 | 0.51925 |
| DarkNet-53 | 0.529491 | 0.54358 | 0.532157 |
| SqueezeNet + DarkNet-53 + MobileNetV2 + Xception + ShuffleNet | 0.897339 | 0.902605 | 0.894416 |
| EfficentNetB7 | 0.513148 | 0.532155 | 0.532913 |
| DCGAN | 0.949983 | 0.940607 | 0.957902 |
| LSTMCNN | 0.966804 | 0.964544 | 0.964641 |
| U-Net(Glaucoma) | 0.962745 | 0.959091 | 0.950293 |
| Proposed Model | 0.945833 | 0.960826 | 0.946373 |
| COVID research paper | 0.961163 | 0.957247 | 0.962947 |
| NASNetLarge | 0.959736 | 0.957844 | 0.954607 |
| DarkNet-53 + MobileNetV2 + Resnet-101 + NASNetLarge + Xception + GoogLeNet | 0.968263 | 0.95837 | 0.965129 |