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對抗樣本(論文解讀九):Making an Invisibility Cloak Real World Adversarial Attacks on Object
時間 2021-01-03
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Machine learning
Deep learning
對抗樣本
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Making an Invisibility Cloak Real World Adversarial Attacks on Object Zuxuan Wu Facebook AI University of Maryland Ser-Nam Lim Facebook AI Larry Davis University of Maryland Tom Goldstein Facebook AI
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相關文章
1.
對抗樣本(論文解讀七):On Physical Adversarial Patches for Object Detection
2.
對抗樣本(論文解讀八):Towards More Robust Adversarial Attack Against Real World Object Detectors
3.
對抗樣本(論文解讀一): DPATCH: An Adversarial Patch Attack on Object Detectors
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對抗樣本(論文解讀二): Transferable Adversarial Attacks for Image and Video Object Detection
5.
對抗樣本(論文解讀三): Adversarial Examples Improve Image Recognition
6.
對抗樣本(論文解讀四): Adversarial Attacks and Defenses in Images, Graphs and Text: A Review
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對抗樣本(論文解讀六):Adversarial camera stickers: A physical camera-based attack on deep learning systems
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Adversarial Examples 對抗樣本
9.
對抗樣本(論文解讀五):Perceptual-Sensitive GAN for Generating Adversarial Patches
10.
【生成對抗樣本】Simple Black-Box Adversarial Attacks on Deep Neural Networks
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相關文章
1.
對抗樣本(論文解讀七):On Physical Adversarial Patches for Object Detection
2.
對抗樣本(論文解讀八):Towards More Robust Adversarial Attack Against Real World Object Detectors
3.
對抗樣本(論文解讀一): DPATCH: An Adversarial Patch Attack on Object Detectors
4.
對抗樣本(論文解讀二): Transferable Adversarial Attacks for Image and Video Object Detection
5.
對抗樣本(論文解讀三): Adversarial Examples Improve Image Recognition
6.
對抗樣本(論文解讀四): Adversarial Attacks and Defenses in Images, Graphs and Text: A Review
7.
對抗樣本(論文解讀六):Adversarial camera stickers: A physical camera-based attack on deep learning systems
8.
Adversarial Examples 對抗樣本
9.
對抗樣本(論文解讀五):Perceptual-Sensitive GAN for Generating Adversarial Patches
10.
【生成對抗樣本】Simple Black-Box Adversarial Attacks on Deep Neural Networks
>>更多相關文章<<