Table 3.7.
Comparison of the proposed model with various other binary classification models.
| Study | Image Type | Method Used | Accuracy |
|---|---|---|---|
| Proposed Model | Chest X-Ray | MobileNet_V2 | 96.33% |
| Ying et al. | Chest CT | DRE-Net | 86.00% |
| Wang et al. | Chest CT | M-Inception | 82.90% |
| Hemdan et al. | Chest X-Ray | COVIDX-Net | 90.00% |
| Sethy and Behra | Chest X-Ray | ResNet50 + SVM | 95.38% |
| Narin et al. | Chest X-Ray | Deep CNN ResNet-50 |
98.00% |
| Zheng et al. | Chest CT | UNet + 3D Deep Network | 90.80% |
| A.S. Al-Waisy et al. | Chest X-Ray | COVID-CheXNet | 99.99% |