This project forked from jiarunliu/co-correcting
License: Apache License 2.0
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 0.2or you can train Co-Correcting with .sh:
sh script/mnist.sh
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