Comments (2)
Hi Liu! I hope my email replies were sufficient for you - as I said, the FTL is a polynomial loss function, there are sometimes stability issues that I mitigated using deep supervision (as an averaging method) and early stopping and model checkpointing (to get the best model as the loss convergence was not always stable) and parameter initialization (used in this repo). Hope this helps any future research directions! :)
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Dear Nabila Abraham:
I have a question about your paper, when i run your codes, the ISIC dataset result can be able to reach the scope of the paper dsc: 0.849 ~ 0.863, but the bus dataset B result is uncertain and can't achieve the results in the paper dsc: 0.78 ~ 0.839. Do you konw why?
the paper mention the experiment is 5-fold cross-validation, it says your hyperparameters got through this?
HI,could you share the link of these two dataset?
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Related Issues (20)
- results HOT 7
- Version issue HOT 8
- gt_train issue HOT 1
- seek for help about the visualization of the CAM of attention unet HOT 2
- need guidance
- ValueError: continuous format is not supported HOT 1
- About the dataset HOT 1
- Multi class support HOT 2
- There is a problem to be solved HOT 3
- About ISIC dataset's folders.
- What does 'thresh' stand for? HOT 1
- Batch_Size HOT 1
- Learning Rate Decay or Typo?
- pred1 output nan after a few epochs
- Unet gating signal typo?
- val_dsc is bigger than 1? HOT 1
- loss: Nan. HOT 2
- Loss calculated on wrong dimension
- Gating Signal before Convolution
- multi-scale input in the attn_reg function
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