blur-training

Training CNNs(Convolutional Neural Networks) with blurred images.
Sou Yoshihara, Taiki Fukiage, Shin'ya Nishida, "Does training with blurred images bring convolutional neural networks closer to humans with respect to robust object recognition and internal representations?", Front. Psychol., Vol. 14,2023

Blurred images (GaussianBlur)

Training images are blurred by Gaussian function. The images are more blurred as std.(σ) of Gaussian kernel is bigger.

Schedule

You can try different training schedule as for blurring images. Here is an overview of the training schedule:
(In ./cifar10/, the terms are different, and some modes may not be included.)

Training

• src/train_imagenet1000.py: Training with ImageNet dataset. See ./training_with_imagenet1000.md/
• src/train_imagenet16.py: Training with 16-class-ImageNet dataset. See ./training_with_imagenet16.md/
• ./cifar10/main.py: Training with Cifar-10 dataset. See ./cifar10/

Datasets

(Note that you have to download ImageNet by yourself.)

• ImageNet dataset
• 16-class-ImageNet dataset This dataset is from Geirhos et al., 2018.
  (R. Geirhos, C. R. M. Temme, J. Rauber, H. H. Schütt, M. Bethge and F. A. Wichmann: Generalisation in humans and deep neural networks. Advances in Neural Information Processing Systems (NeurIPS), 7538–7550, 2018.)
  I make the dataset from ImageNet by using robustness library.
• Cifar-10 dataset

References

pytorch tutorial
pytorch imagenet training example