Table 4 Results of the ResNet-152 architecture
From: Tongue image quality assessment based on a deep convolutional neural network
Folds | Precision | Recall | F1-score | Accuracy |
|---|---|---|---|---|
Fold 1 | 99.21% | 99.21% | 99.21% | 99.21% |
Fold 2 | 98.04% | 98.02% | 98.03% | 98.03% |
Fold 3 | 98.45% | 98.41% | 98.43% | 98.43% |
Fold 4 | 98.83% | 98.81% | 98.82% | 98.82% |
Fold 5 | 98.42% | 98.42% | 98.42% | 98.43% |
Fold 6 | 98.81% | 98.83% | 98.82% | 98.82% |
Fold 7 | 99.21% | 99.21% | 99.21% | 99.21% |
Fold 8 | 98.83% | 98.81% | 98.82% | 98.82% |
Fold 9 | 99.24% | 99.19% | 99.22% | 99.21% |
Fold 10 | 99.24% | 99.19% | 99.22% | 99.21% |
Average (SD) | 98.83% (0.42%) | 98.81% (0.42%) | 98.82% (0.42%) | 98.82% (0.41%) |