Table 5 Performance of VGG16
From: Forest fire and smoke detection using deep learning-based learning without forgetting
Types of images | Accuracy (%) | Precision (%) | Recall (%) | F1 score (%) | ||||
|---|---|---|---|---|---|---|---|---|
FE | FT | FE | FT | FE | FT | FE | FT | |
Fire | 92.63 | 93.75 | 86.15 | 88.66 | 84 | 86 | 85.06 | 87.31 |
Smoke | 93.63 | 95.88 | 84.33 | 95.63 | 91.5 | 87.5 | 87.77 | 91.38 |
Smoke fire | 92.75 | 95 | 85.5 | 90.4 | 85.5 | 89.5 | 85.5 | 89.95 |
No fire | 89 | 90.63 | 79.79 | 77.78 | 75 | 87.5 | 77.32 | 82.35 |