Dear Xingjun:
I have tried your method to train the 12-layer-cnn on CIFAR-10 with 20% noise rate,I also observe the decrease and increase of LID score. but in my experiment. the test accuracy is 88.34% by just using cross-entropy as loss function. (in your paper is 73.12%) for 40% noise rate the test accuracy is 84.88% (65.07% in your paper),the results is even better than the results using your D2L method. the only difference during the training process may lies on the preprocessing of the training image (what I use is described in the loss correction method CVPR'17). I wonder why the difference is so much and whether you can try the preprocessing method as in CVPR'17 and train the network again.
Thanks !
Dear Xingjun:
I have tried your method to train the 12-layer-cnn on CIFAR-10 with 20% noise rate,I also observe the decrease and increase of LID score. but in my experiment. the test accuracy is 88.34% by just using cross-entropy as loss function. (in your paper is 73.12%) for 40% noise rate the test accuracy is 84.88% (65.07% in your paper),the results is even better than the results using your D2L method. the only difference during the training process may lies on the preprocessing of the training image (what I use is described in the loss correction method CVPR'17). I wonder why the difference is so much and whether you can try the preprocessing method as in CVPR'17 and train the network again.
Thanks !