Table 3 Comparison of nuclear segmentation between the fused ENet with UNet, fused UNet, and multitask learning
From: Fusion of encoder-decoder deep networks improves delineation of multiple nuclear phenotypes
Input size | Recall | Precision | F1-Score | Standard Error |
|---|---|---|---|---|
UNet | 0.86 | 0.81 | 0.83 | 1.2786e-06 |
Fused-UNet | 0.89 | 0.86 | 0.87 | 1.1921e-06 |
Multi-task UNet | 0.87 | 0.77 | 0.81 | 1.3117e-06 |
ENet | 0.83 | 0.88 | 0.84 | 1.1412e-06 |
Fused-ENet | 0.94 | 0.88 | 0.91 | 1.1124e-06 |
Multi-task ENet | 0.89 | 0.83 | 0.86 | 1.2690e-06 |