Research Article
Digital Forensics Use Case for Glaucoma Detection Using Transfer Learning Based on Deep Convolutional Neural Networks
Table 3
Validation accuracy, validation loss, and training accuracy of different deep learning neural networks.
| ā | DenseNet201 | EfficientNetB7 | InceptionV3 | NASNetMobile | ResNet50 | ResNet101V2 | ResNet152 | VGG16 |
| Validation accuracy (%) | 0.12 | 100.00 | 96.47 | 26.56 | 56.64 | 7.87 | 99.65 | 26.32 | Validation loss | 0.69315 | 0.6931 | 0.6931 | 0.6931 | 0.6931 | 0.6932 | 0.6931 | 0.6931 | Training accuracy (%) | 0.50 | 0.50 | 0.49 | 0.49 | 0.50 | 0.51 | 0.50 | 0.51 |
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