Comments (1)
Basically, given an ImageNet test image, we first generate the adversarial example via FGSM, and then test the generated adversarial example to see if the model could correctly classify it. You could check the code here to see the details.
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Related Issues (11)
- Question about training dataset HOT 2
- Shape and Texture biased pretrain models HOT 16
- imagenet-a HOT 2
- Ensemble of two models HOT 1
- StyleTransfer problem HOT 3
- Question about the label of style for original image
- CAM to visualize which image regions are attended by models
- FileNotFoundError: Couldn't find any class folder in C:/datasets/ILSVRC/Data/CLS-LOC\val HOT 1
- RuntimeError: No CUDA GPUs are available HOT 2
- Models trained and evaluated on ImageNet-200 are Center Cropped to 224?
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