Semantic Segmentation on ISIC 2017 (val)
79.6IoUFully supervised
Evaluation results
| Method | Links | |
|---|---|---|
| Fully supervisedBackbone=DenseUNet-161, Pre-training=ImageNet, Supervised Samples=2000, Source=Results from [25]2019.06 | 79.6 | |
| Fully supervisedBackbone=DenseUNet-161, Pre-training=ImageNet, Supervised Samples=2000, Source=Our results2019.06 | 78.61 | |
| Std. aug.Backbone=DenseUNet-161, Pre-training=ImageNet, Supervised Samples=50, Source=Results from [25]2019.06 | 75.31 | |
| CutMixBackbone=DenseUNet-161, Pre-training=ImageNet, Supervised Samples=50, Source=Our results2019.06 | 74.57 | |
| BaselineBackbone=DenseUNet-161, Pre-training=ImageNet, Supervised Samples=50, Source=Results from [25]2019.06 | 72.85 | |
| Std. aug.Backbone=DenseUNet-161, Pre-training=ImageNet, Supervised Samples=50, Source=Our results2019.06 | 71.4 | |
| VATBackbone=DenseUNet-161, Pre-training=ImageNet, Supervised Samples=50, Source=Our results2019.06 | 69.09 | |
| CutoutBackbone=DenseUNet-161, Pre-training=ImageNet, Supervised Samples=50, Source=Our results2019.06 | 68.76 | |
| BaselineBackbone=DenseUNet-161, Pre-training=ImageNet, Supervised Samples=50, Source=Our results2019.06 | 67.64 | |
| ICTBackbone=DenseUNet-161, Pre-training=ImageNet, Supervised Samples=50, Source=Our results2019.06 | 65.45 |