Tumor Classification on Brain MRI scans
97AccuracyResNet18 (Transfer Learning)
Evaluation results
| Method | Links | ||||
|---|---|---|---|---|---|
| ResNet18 (Transfer Learning)Study=Proposed Work, Methodology=Transfer Learning2026.06 | 97 | 97.2 | 96.8 | 97 | |
| U-Net with ResNet50 EncoderStudy=[8]2026.06 | 96.1 | 96.8 | 95.4 | 96 | |
| ResNet50 (Transfer Learning)Study=Proposed Work, Methodology=Transfer Learning2026.06 | 96 | 96.1 | 95.9 | 96 | |
| Pretrained CNN Models (Transfer Learning)Study=[11], Methodology=Transfer Learning2026.06 | 95.6 | 96.2 | 95 | 95 | |
| ResNet50 + Grad-CAM (Explainable AI)Study=[6], Type=Explainable AI2026.06 | 95.2 | 95.6 | 94.8 | 95 | |
| Proposed CNNPre-trained on=Kidney dataset, Pre-training Epochs=752026.06 | 92.54 | 91.02 | 94.87 | 92.71 | |
| VGG16Training Strategy=Retrained for 20 epochs2026.06 | 91.17 | 84.33 | 98 | 91.73 | |
| Proposed CNNPre-trained on=Lung dataset, Pre-training Epochs=752026.06 | 89.88 | 84.84 | 94.92 | 90.38 | |
| VGG19Training Strategy=Retrained for 20 epochs2026.06 | 89.67 | 84.67 | 94.67 | 90.16 | |
| MobileNetV2Training Strategy=Retrained for 20 epochs2026.06 | 78.67 | 80.33 | 77 | 78.31 | |
| DenseNet121Training Strategy=Retrained for 20 epochs2026.06 | 78.5 | 77.33 | 79.67 | 78.75 | |
| XceptionTraining Strategy=Retrained for 20 epochs2026.06 | 57.5 | 21.67 | 93.33 | 68.71 |