Table 4 The resulting precision, recall, and f1-score values for Scenario 1 (training the algorithms with all training datasets and testing them on the Taiwan, China, Japan, and all test datasets separately).
U-Net | ResU-Net | |||||
|---|---|---|---|---|---|---|
Size | 32 | 64 | 128 | 32 | 64 | 128 |
Precision | 67.45 | 63.95 | 64.32 | 66.39 | 69.65 | 60.11 |
Recall | 58.97 | 67.13 | 61.39 | 6543 | 63.85 | 74.29 |
F1-score | 62.93 | 65.5 | 62.82 | 65.91 | 66.63 | 66.45 |
Precision | 65.47 | 60.48 | 59.73 | 64.99 | 68.11 | 57.21 |
Recall | 77.52 | 84.16 | 80.24 | 78.94 | 78.51 | 88.38 |
F1-score | 70.99 | 70.38 | 68.48 | 71.29 | 72.94 | 69.46 |
Precision | 79.76 | 70.27 | 81.2 | 75.02 | 74.74 | 65.57 |
Recall | 55.52 | 61.85 | 55.48 | 59.04 | 60.33 | 64.3 |
F1-score | 65.47 | 65.79 | 65.92 | 66.07 | 66.76 | 64.93 |
Precision | 69.26 | 68.35 | 70.8 | 67.33 | 71.12 | 63.41 |
Recall | 44.05 | 53.62 | 46.33 | 54.92 | 52.14 | 63.43 |
F1-score | 53.85 | 60.1 | 56.01 | 60.49 | 60.17 | 63.42 |
Algorithms trained by sample from | All | Taiwan | China | Japan | ||
