Table 3.
Comparison of the most commonly used automatic diagnosis of COVID-19 that are based on chest X-ray images to our fine-tuned models
| Study | Architecture | Accuracy | Number of parameters in Million |
|---|---|---|---|
| Sethy and Behra [25] | Resnet50 | 95.38 % | 36 |
| Narin et al. [20] | InceptionV3 | 97 % | 26 |
| Ioannis et al. [3] | Xception | 85.57 % | 33 |
| Ozturk et al. [21] | DarkNet | 98.08 % | 1.1 |
| Ioannis et al. [3] | VGG19 | 98.75 % | 143 |
| Fine-tuned Resnet50 | Resnet50 | 97.20 % | 23 |
| Fine-tuned VGG16 | VGG16 | 98.30 % | 15 |
| Fine-tuned InceptionV3 | InceptionV3 | 98.10 % | 21 |