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Hi! Thanks for sharing your work.
I replicated the paper's code, but the results astonished me. My training and testing Dice results exceeded those in the original paper by a significant margin, and I don't know why! I used the 2D Abdomen MR dataset and training environment provided by the paper. I suspect that the training process automatically loads the authors' pre-trained model, allowing the results to achieve great performance after about 30 epochs.
Could you provide the progress.png image of your training results?
The text was updated successfully, but these errors were encountered:
Hi! Thanks for sharing your work. I replicated the paper's code, but the results astonished me. My training and testing Dice results exceeded those in the original paper by a significant margin, and I don't know why! I used the 2D Abdomen MR dataset and training environment provided by the paper. I suspect that the training process automatically loads the authors' pre-trained model, allowing the results to achieve great performance after about 30 epochs. Could you provide the progress.png image of your training results?
Hi, this is the same thing I am experiencing too. Did you found what the reason is?
Hi! Thanks for sharing your work.
I replicated the paper's code, but the results astonished me. My training and testing Dice results exceeded those in the original paper by a significant margin, and I don't know why! I used the 2D Abdomen MR dataset and training environment provided by the paper. I suspect that the training process automatically loads the authors' pre-trained model, allowing the results to achieve great performance after about 30 epochs.
Could you provide the progress.png image of your training results?
The text was updated successfully, but these errors were encountered: