Table 7.
Five-fold test performance of four transfer learning models on the dataset.
| Architectures | Class | Precision | Recall | F1 score | Accuracy |
|---|---|---|---|---|---|
| ResNet152 | Pituitary | 1 | 0.93 | 0.98 | 0.985 |
| Normal | 0.98 | 1 | 0.97 | ||
| Meningioma | 1 | 1 | 1 | ||
| Glioma | 0.96 | 1 | 0.99 | ||
| Total | 3.94 | 3.93 | 3.94 | ||
| VGG19 | Pituitary | 1 | 1 | 0.95 | 0.960 |
| Normal | 0.95 | 0.92 | 0.95 | ||
| Meningioma | 1 | 1 | 1 | ||
| Glioma | 0.93 | 1 | 0.94 | ||
| Total | 3.88 | 3.92 | 3.84 | ||
| DenseNet169 | Pituitary | 1 | 0.85 | 0.94 | 0.9675 |
| Normal | 0.88 | 1 | 0.93 | ||
| Meningioma | 1 | 1 | 1 | ||
| Glioma | 1 | 1 | 1 | ||
| Total | 3.88 | 3.85 | 3.87 | ||
| MobileNetv3 | Pituitary | 1 | 1 | 1 | 0.960 |
| Normal | 1 | 0.83 | 0.92 | ||
| Meningioma | 1 | 1 | 1 | ||
| Glioma | 0.88 | 1 | 0.92 | ||
| Total | 3.88 | 3.83 | 3.84 |