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Examples

Noisy from Human

Noise Type aggre rand1 rand2 rand3 worst noisy100
Noise Rate(%) 9.03 17.23 18.12 17.64 40.21 40.2

Type noisy100 belongs to cifar100, and other types belong to cifar10.

python main.py --dataset cifar10 --human --noise_type aggre
python main.py --dataset cifar100 --human --noise_type noisy100

Noisy from Synthesis

symmetric noise:

  • sym to generate symmetric noise, otherwise asymmetric noise.
  • noise_rate is the noise rate of the dataset.
python main.py --dataset cifar10 --sym --noise_rate 0.5
python main.py --dataset cifar100 --sym --noise_rate 0.5

asymmetric noise:

  • cifar10: the noisy samples are flipped in some classes i.e. automobile < - truck, bird -> airplane, cat <-> dog, deer -> horse
  • cifar100: the noisy samples are flipped in same superclass.
python main.py --dataset cifar10 --noise_rate 0.5
python main.py --dataset cifar100 --noise_rate 0.5

Others

  • Under the same resnet structure, the resnet provided by torchvision will reduce performance compared to the custom resnet. (Why?)
  • Issue is welcomed.

Reference

  1. cifar-10-100n
  2. SCELoss-Reproduce

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Cifar with Noisy from Human or Synthesis

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