Table 8. Comparison of the proposed ECOVNet with other state-of-the-art methods on COVID-19 detection.
Method | Precision (%) (COVID-19) | Recall (%) (COVID-19) | Accuracy (%) |
---|---|---|---|
COVID-Net (Wang, Lin & Wong, 2020) | 92.80 | 91.00 | 93.92 |
EfficientNet-B3 (Luz et al., 2020) | 95.29 | 81.00 | 94.49 |
DarkCovidNet (Ozturk et al., 2020) | 96.00 | 88.00 | 92.00 |
CoroNet (Khan, Shah & Bhat, 2020) | 91.00 | 87.00 | 88.00 |
ECOVNet-Hard Ensemble (Proposed) | 94.17 | 97.00 | 96.07 |
ECOVNet-Soft Ensemble (Proposed) | 92.59 | 100 | 96.07 |
Note:
Bold indicates that the method has statistically better performance than other methods.