Table 1. Comparison of several variations of DoGNets and several baselines on PRISM dataset.
Method | # params | F1 Score | Precision | Recall | AUC | |DiC| |
---|---|---|---|---|---|---|
ConvNets | ||||||
Direct | 3392 | 0.74 | 0.66 | 0.84 | 0.85 | 17.67 |
FCN | 3002 | 0.75 | 0.73 | 0.77 | 0.84 | 7.44 |
Unet | 622 | 0.80 | 0.78 | 0.83 | 0.88 | 10.44 |
DoGNets | ||||||
Shallow Isotropic | 62 | 0.78 | 0.72 | 0.87 | 0.91 | 15.22 |
Shallow Anisotropic | 107 | 0.83 | 0.81 | 0.86 | 0.91 | 4.89 |
Deep Isotropic | 140 | 0.81 | 0.81 | 0.82 | 0.89 | 9.78 |
Deep Anisotropic | 230 | 0.80 | 0.81 | 0.80 | 0.83 | 7.89 |
Manually tuned methods | ||||||
Nieland 2014 [38] | - | 0.78 | 0.72 | 0.84 | 0.82 | 1. |
Simhal 2017 [32] | - | 0.50 | 0.45 | 0.58 | 0.68 | 21. |