Table 1 Comparison of performance when COVID-19 is considered a positive class.
From: The shallowest transparent and interpretable deep neural network for image recognition
Base | Metric | Our | Base only | |||||
|---|---|---|---|---|---|---|---|---|
VGG-16 | Accuracy | 86.24 | 86.12 | 86.01 | 85.89 | 84.63 | 79.73 | 82.45 |
Precision | 0.96 | 0.98 | 0.99 | 0.99 | 0.97 | 0.87 | 0.97 | |
Recall | 0.94 | 0.99 | 0.99 | 0.98 | 0.99 | 0.92 | 0.98 | |
F1-score | 0.95 | 0.98 | 0.99 | 0.98 | 0.97 | 0.89 | 0.97 | |
VGG-19 | Accuracy | 86.24 | 83.94 | 84.98 | 84.40 | 88.99 | 81.78 | 82.68 |
Precision | 0.96 | 0.98 | 0.98 | 0.99 | 0.91 | 0.84 | 0.96 | |
Recall | 0.94 | 0.99 | 0.98 | 0.98 | 0.96 | 0.95 | 0.98 | |
F1-score | 0.95 | 0.98 | 0.98 | 0.98 | 0.93 | 0.89 | 0.97 | |
ResNet-34 | Accuracy | 86.24 | 85.77 | 85.55 | 85.20 | 84.29 | 82.90 | 84.89 |
Precision | 0.96 | 0.98 | 0.99 | 0.99 | 0.99 | 0.99 | 0.99 | |
Recall | 0.94 | 0.99 | 0.99 | 0.98 | 0.99 | 0.99 | 0.99 | |
F1-score | 0.95 | 0.99 | 0.99 | 0.98 | 0.99 | 0.98 | 0.99 | |
ResNet-152 | Accuracy | 86.24 | 88.30 | 86.93 | 86.70 | 86.40 | 83.60 | 88.03 |
Precision | 0.96 | 0.99 | 0.98 | 0.98 | 0.99 | 0.87 | 0.98 | |
Recall | 0.94 | 0.98 | 0.99 | 0.99 | 0.99 | 0.89 | 0.99 | |
F1-score | 0.95 | 0.98 | 0.99 | 0.98 | 0.99 | 0.88 | 0.98 | |
DenseNet-121 | Accuracy | 86.24 | 87.50 | 87.27 | 87.04 | 86.47 | 85.90 | 88.41 |
Precision | 0.96 | 0.99 | 0.99 | 0.98 | 0.99 | 0.98 | 0.99 | |
Recall | 0.94 | 0.99 | 0.99 | 0.99 | 0.98 | 0.98 | 0.99 | |
F1-score | 0.95 | 0.99 | 0.99 | 0.98 | 0.98 | 0.98 | 0.99 | |
DenseNet-161 | Accuracy | 86.24 | 88.07 | 87.39 | 87.27 | 87.04 | 86.58 | 88.42 |
Precision | 0.96 | 0.99 | 0.99 | 0.97 | 0.97 | 0.95 | 0.99 | |
Recall | 0.94 | 0.99 | 0.99 | 0.99 | 0.99 | 0.96 | 0.99 | |
F1-score | 0.95 | 0.99 | 0.99 | 0.97 | 0.97 | 0.96 | 0.99 |
