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In [adversarial_attacks_pytorch.py](https://github.com/Trusted-AI/adversarial-robustness-toolbox/blob/main/art/attacks/evasion/adversarial_patch/adversarial_patch_pytorch.py) line 191 : `loss.backward…
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## 論文リンク
https://arxiv.org/pdf/1511.04508.pdf
## 概要
Knowledge DistillationをAdversarial Exampleの防御手段として利用した論文
## 手法のキモ
生徒モデルを教師モデルと同じアーキテクチャとし、教師モデルの学習時と知識蒸留時は温度Tつきsoftmaxを通した後のクロスエン…
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> The discovery of adversarial examples has raised concerns about the practical deployment of deep learning systems. In this paper, we argue that the field of medicine may be uniquely susceptible to a…
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hello i found that in your code you save images as '.bmp'. i changed the code to save images as '.jpg' and found minigpt4 said the saved adversarial images are blurred and pixelated, which suggests th…
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The current Randomized Smoothing is a generic method, that we use the averaged logits of samples from Gaussian distribution as the prediction result. However, according to [Certified Adversarial Robus…
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## URL(s) with the issue:
https://www.tensorflow.org/api_docs/python/tf/image/resize
## Description of issue:
TensorFlow is vulnerable to image-scaling attacks if specific scaling algorithms an…
EQuiw updated
3 months ago
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Thanks for releasing such a rigorous evaluation of existing works on adversarial defenses. It is immensely helpful to get more clarity on this topic. I wonder what is the criterion to add new models t…
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I wanna to know how to use my own picture dataset to get the model which defenses Adversarial Attacks.How could I change the code to train my own dataset?
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When I debug the `PGDtraining`, I find that requires_grad of adversarial data is true.
Is that right? The input image may be not allowed to require grad.
https://github.com/DSE-MSU/DeepRobust/…
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When evaluating whether inputs are adversarial, the framework first checks whether the classification of the input matches the groundtruth label. If it does not, then it uses the detection mechanism t…