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Jiarun Liu 4e3ca4951d | 2 years ago | |
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dataset | 3 years ago | |
models | 3 years ago | |
scripts | 3 years ago | |
utils | 3 years ago | |
BasicTrainer.py | 3 years ago | |
Co-Correcting.py | 3 years ago | |
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Loss.py | 3 years ago | |
README.md | 2 years ago |
Official implementation of TMI 2021 paper Co-Correcting: Noise-tolerant Medical Image Classification via collaborative Label Probability Estimation [paper][arxiv]
Co-Correcting.py
is used for both training a model on dataset with noisy labels and validating it.
Here is an example:
python Co-Correcting.py --dir ./experiment/ --dataset 'mnist' --noise_type sn --noise 0.2 --forget-rate 0.2
or you can train Co-Correcting with .sh
:
sh script/mnist.sh
Co-Correcting: Noise-tolerant Medical Image Classification via collaborative Label Probability Estimation (TMI 2021)
Python Shell
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