Table 4 Performance of different depth in MLES-Nets (%)
From: Detecting COVID-19 patients via MLES-Net deep learning models from X-Ray images
| Â | Accuracy | Precision | Recall | Specificity | F1-Measure | COVID-19-Acc |
|---|---|---|---|---|---|---|
MLES-40 | ||||||
FC GAP GAPFC | 92.01 91.05 92.98 | 95.07 92.03 95.40 | 91.78 90.50 92.65 | 94.39 94.28 94.40 | 93.40 91.26 94.00 | 99.02 95.10 98.00 |
MLES-56 | ||||||
FC GAP GAPFC | 92.56 91.46 95.27 | 95.59 94.58 96.91 | 92.11 91.14 94.66 | 94.74 94.07 96.49 | 93.82 92.82 95.77 | 98.00 98.00 100.00 |
MLES-107 | ||||||
FC GAP GAPFC | 92.70 91.73 93.39 | 94.98 95.05 96.12 | 92.42 91.44 93.28 | 95.01 94.28 95.30 | 93.68 93.21 94.67 | 98.00 99.02 100.00 |