Interpreting Adversarially Trained Convolutional Neural Networks
個人總結： 其實說白了就是： AT-CNNs are more biased towards global structures, such as shapes and edges。 AT-CNN對圖像的整體結構，比如形狀，邊緣更加敏感，可以更好的捕捉到這些信息。 AT-CNNs are less sensitive to the texture distortion and foc
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相關文章
- 1. 可解釋的對抗訓練網絡模型：Interpreting Adversarially Trained Convolutional Neural Networks-ICML 2019
- 2. Convolutional Neural Networks---Foundations of Convolutional Neural Networks
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- 4. Convolutional Neural Networks: Application
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- 6. Convolutional Neural Networks-Week1
- 7. Convolutional Neural Networks
- 8. Orthogonal Convolutional Neural Networks
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- 10. Convolutional Neural Networks - Week4