Table 7 The resulting precision, recall, and f1-score values for Scenario 4 (training the algorithms with the training dataset of Japan and testing on the Taiwan, China, Japan, and all test datasets separately).
U-Net | ResU-Net | |||||
|---|---|---|---|---|---|---|
Size | 32 | 64 | 128 | 32 | 64 | 128 |
Precision | 44.13 | 32.01 | 48.56 | 42.16 | 61.03 | 41.14 |
Recall | 56.46 | 66.64 | 56.97 | 57.31 | 47.01 | 63.58 |
F1-score | 49.54 | 43.25 | 52.43 | 48.58 | 53.11 | 49.95 |
Precision | 28.75 | 21.72 | 35.17 | 27.07 | 42.34 | 29.58 |
Recall | 51.46 | 80.87 | 59.38 | 52.51 | 24.7 | 73.95 |
F1-score | 36.89 | 34.24 | 44.17 | 35.73 | 31.2 | 42.26 |
Precision | 63.52 | 63.46 | 67.96 | 67.47 | 71.82 | 62.95 |
Recall | 80.18 | 78.3 | 74.18 | 73.55 | 74.88 | 73.55 |
F1-score | 70.89 | 70.1 | 70.93 | 70.38 | 73.32 | 67.84 |
Precision | 67.58 | 66.44 | 70.89 | 66.53 | 69.85 | 68.91 |
Recall | 58.51 | 53.89 | 53.85 | 59.36 | 62.79 | 54.35 |
F1-score | 62.72 | 59.51 | 61.21 | 62.74 | 66.13 | 60.77 |
Algorithms trained by sample from | All | Taiwan | China | Japan | ||
