U-Net: Convolutional Networks for Biomedical Image Segmentation
https://arxiv.org/abs/1505.04597
Recurrent Residual Convolutional Neural Network based on U-Net (R2U-Net) for Medical Image Segmentation
https://arxiv.org/abs/1802.06955
Attention U-Net: Learning Where to Look for the Pancreas
https://arxiv.org/abs/1804.03999
Attention R2U-Net : Just integration of two recent advanced works (R2U-Net + Attention U-Net)
we just test the models with ISIC 2018 dataset. The dataset was split into three subsets, training set, validation set, and test set, which the proportion is 70%, 10% and 20% of the whole dataset, respectively. The entire dataset contains 2594 images where 1815 images were used for training, 259 for validation and 520 for testing models.
This code is imported from https://github.com/LeeJunHyun/Image_Segmentation with improvement in vizualization