Retinal Vessel Segmentation On Stare
Metriken
F1 score
Ergebnisse
Leistungsergebnisse verschiedener Modelle zu diesem Benchmark
Vergleichstabelle
| Modellname | F1 score |
|---|---|
| road-extraction-by-deep-residual-u-net | 0.8388 |
| recurrent-residual-convolutional-neural | 0.8475 |
| u-net-convolutional-networks-for-biomedical | 0.8373 |
| full-scale-representation-guided-network-for | 0.8510 |
| rv-gan-retinal-vessel-segmentation-from | 0.8323 |
| resolution-aware-design-of-atrous-rates-for | - |
| dunet-a-deformable-network-for-retinal-vessel | 0.8143 |
| deep-vessel-segmentation-by-learning | 0.8429 |