Table 6.
ACC, F1-score, and Recall comparison of different models in UofO dataset under different SNRs (%).
| SNR (dB) | − 9 | − 6 | − 3 | |||||||
|---|---|---|---|---|---|---|---|---|---|---|
| Model | Noise type | ACC | F1-score | Recall | ACC | F1-score | Recall | ACC | F1-score | Recall |
| MLSCA-CW (two locations) | Gauss-noise | 100.000 | 100.000 | 100.000 | 100.000 | 100.000 | 100.000 | 100.000 | 100.000 | 100.000 |
| Laplace-noise | 100.000 | 100.000 | 100.000 | 100.000 | 100.000 | 100.000 | 100.000 | 100.000 | 100.000 | |
| Violet-noise | 99.744 | 99.744 | 99.744 | 100.000 | 100.000 | 100.000 | 100.000 | 100.000 | 100.000 | |
| Brownian-noise | 95.819 | 95.828 | 95.819 | 96.160 | 96.084 | 96.087 | 96.331 | 96.349 | 96.355 | |
| Mixed-noise | 73.976 | 73.987 | 73.976 | 81.655 | 81.630 | 81.607 | 86.263 | 86.059 | 85.990 | |
| MLSCA-CW (single location) | Gauss-noise | 89.759 | 89.837 | 89.759 | 92.918 | 92.943 | 93.013 | 99.915 | 99.917 | 99.916 |
| Laplace-noise | 88.055 | 87.764 | 88.055 | 99.829 | 99.825 | 99.829 | 99.829 | 99.823 | 99.823 | |
| Violet-noise | 67.491 | 66.903 | 67.491 | 67.662 | 66.959 | 66.957 | 68.515 | 68.431 | 68.515 | |
| Brownian-noise | 69.966 | 70.422 | 69.966 | 71.331 | 71.388 | 71.177 | 78.157 | 77.906 | 77.771 | |
| Mixed-noise | 63.140 | 62.380 | 63.450 | 64.505 | 56.557 | 64.944 | 66.212 | 59.645 | 66.212 | |
| LR | Gauss-noise | 80.887 | 80.857 | 80.887 | 81.399 | 81.206 | 81.686 | 82.594 | 82.203 | 82.594 |
| Laplace-noise | 80.802 | 80.574 | 80.802 | 81.826 | 81.531 | 81.826 | 83.532 | 83.170 | 83.532 | |
| Violet-noise | 62.201 | 60.689 | 62.201 | 65.785 | 62.516 | 64.547 | 68.345 | 67.076 | 68.345 | |
| Brownian-noise | 32.594 | 18.560 | 32.594 | 33.703 | 20.273 | 33.481 | 35.410 | 23.759 | 35.410 | |
| Mixed-noise | 37.500 | 37.080 | 37.500 | 38.225 | 34.837 | 38.225 | 43.345 | 39.934 | 43.078 | |
| MC-CNN | Gauss-noise | 95.734 | 95.737 | 95.734 | 97.440 | 97.438 | 97.440 | 100.000 | 100.000 | 100.000 |
| Laplace-noise | 94.966 | 94.968 | 94.966 | 96.416 | 96.413 | 96.416 | 100.000 | 100.000 | 100.000 | |
| Violet-noise | 81.911 | 81.878 | 81.911 | 85.448 | 85.391 | 85.448 | 92.217 | 92.126 | 92.217 | |
| Brownian-noise | 41.076 | 40.546 | 41.076 | 46.200 | 45.463 | 46.200 | 95.601 | 95.588 | 95.601 | |
| Mixed-noise | 68.174 | 68.443 | 68.174 | 70.734 | 70.804 | 70.734 | 74.147 | 74.209 | 74.147 | |
| WDCNN | Gauss-noise | 73.294 | 73.266 | 73.294 | 74.915 | 74.944 | 74.915 | 99.915 | 99.916 | 99.916 |
| Laplace-noise | 100.000 | 100.000 | 100.000 | 100.000 | 100.000 | 100.000 | 100.000 | 100.000 | 100.000 | |
| Violet-noise | 65.870 | 63.396 | 65.870 | 67.065 | 66.142 | 67.044 | 69.625 | 68.699 | 69.625 | |
| Brownian-noise | 72.952 | 72.924 | 72.952 | 73.294 | 73.418 | 73.175 | 76.024 | 75.754 | 75.671 | |
| Mixed-noise | 68.089 | 68.240 | 68.381 | 70.478 | 70.141 | 70.070 | 73.891 | 73.745 | 73.891 | |
| Multiscale inner product | Gauss-noise | 92.491 | 92.495 | 92.491 | 95.648 | 95.671 | 95.648 | 97.355 | 97.367 | 97.355 |
| Laplace-noise | 89.505 | 89.501 | 89.505 | 92.065 | 92.064 | 92.065 | 94.625 | 94.619 | 94.625 | |
| Violet-noise | 83.959 | 83.930 | 83.959 | 85.666 | 85.646 | 85.666 | 88.225 | 88.208 | 88.225 | |
| Brownian-noise | 91.041 | 91.043 | 91.041 | 92.747 | 92.753 | 92.747 | 95.307 | 95.308 | 95.307 | |
| Mixed-noise | 69.120 | 69.098 | 69.120 | 72.504 | 72.453 | 72.504 | 74.196 | 74.229 | 74.196 | |
| SANet | Gauss-noise | 69.795 | 69.414 | 69.795 | 78.157 | 76.166 | 78.505 | 79.863 | 78.058 | 79.863 |
| Laplace-noise | 68.345 | 58.102 | 68.345 | 69.198 | 59.924 | 69.198 | 71.758 | 64.939 | 71.758 | |
| Violet-noise | 66.638 | 64.001 | 66.638 | 67.065 | 67.083 | 67.199 | 68.601 | 68.450 | 68.601 | |
| Brownian-noise | 52.986 | 52.579 | 52.986 | 55.205 | 51.545 | 55.219 | 56.911 | 53.621 | 56.911 | |
| Mixed-noise | 53.840 | 53.528 | 54.046 | 55.034 | 54.700 | 54.862 | 58.106 | 57.489 | 58.106 | |
| QCNN | Gauss-noise | 99.829 | 99.829 | 99.829 | 100.000 | 100.000 | 100.000 | 100.000 | 100.000 | 100.000 |
| Laplace-noise | 100.000 | 100.000 | 100.000 | 100.000 | 100.000 | 100.000 | 100.000 | 100.000 | 100.000 | |
| Violet-noise | 67.235 | 66.850 | 67.235 | 69.113 | 67.640 | 68.070 | 70.819 | 70.205 | 70.819 | |
| Brownian-noise | 52.218 | 52.018 | 52.218 | 54.181 | 49.979 | 54.194 | 56.485 | 56.316 | 56.485 | |
| Mixed-noise | 72.696 | 72.369 | 72.696 | 74.061 | 73.675 | 73.680 | 75.341 | 75.333 | 75.341 | |
Best results is highlighted