Table 6.
Evaluation of deep features combined with traditional algorithms from the literature and stain normalization on non-segmented images
| LOG | RF | SVM | |||||
|---|---|---|---|---|---|---|---|
| Method | Reference | F1 | F1 | F1 | |||
| No normalization | - | 86.44 | 0.83 | 90.93 | 0.88 | 87.73 | 0.82 |
| Macenko et al. [42] | Ref-1 | 86.62 | 0.83 | 91.17 | 0.88 | 89.84 | 0.86 |
| Ref-2 | 88.86 | 0.85 | 92.26 | 0.89 | 89.33 | 0.86 | |
| Ref-3 | 88.94 | 0.85 | 91.23 | 0.88 | 90.42 | 0.88 | |
| Reinhard et al. [43] | Ref-1 | 80.33 | 0.78 | 83.22 | 0.81 | 82.12 | 0.79 |
| Ref-2 | 84.13 | 0.81 | 85.15 | 0.83 | 89.78 | 0.84 | |
| Ref-3 | 83.28 | 0.81 | 85.83 | 0.84 | 85.34 | 0.81 | |
| Tosta et al. [28] | Ref-1 | 85.70 | 0.83 | 87.96 | 0.85 | 87.96 | 0.85 |
| Ref-2 | 88.53 | 0.85 | 89.34 | 0.86 | 88.73 | 0.85 | |
| Ref-3 | 83.31 | 0.81 | 85.64 | 0.83 | 85.91 | 0.82 | |
| Vahadane et al. [27] | Ref-1 | 85.63 | 0.82 | 87.04 | 0.84 | 86.29 | 0.83 |
| Ref-2 | 86.07 | 0.84 | 86.92 | 0.84 | 88.12 | 0.85 | |
| Ref-3 | 87.13 | 0.84 | 89.08 | 0.86 | 89.23 | 0.86 | |