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ComDefend: An Efficient Image Compression Model to Defend Adversarial
  Examples

ComDefend: An Efficient Image Compression Model to Defend Adversarial Examples

30 November 2018
Xiaojun Jia
Xingxing Wei
Xiaochun Cao
H. Foroosh
    AAML
ArXivPDFHTML

Papers citing "ComDefend: An Efficient Image Compression Model to Defend Adversarial Examples"

3 / 3 papers shown
Title
Towards Model Resistant to Transferable Adversarial Examples via Trigger Activation
Towards Model Resistant to Transferable Adversarial Examples via Trigger Activation
Yi Yu
Song Xia
Xun Lin
Chenqi Kong
Wenhan Yang
Shijian Lu
Yap-Peng Tan
Alex C. Kot
AAML
SILM
52
0
0
20 Apr 2025
Parallel Rectangle Flip Attack: A Query-based Black-box Attack against
  Object Detection
Parallel Rectangle Flip Attack: A Query-based Black-box Attack against Object Detection
Siyuan Liang
Baoyuan Wu
Yanbo Fan
Xingxing Wei
Xiaochun Cao
AAML
11
69
0
22 Jan 2022
Adversarial Machine Learning at Scale
Adversarial Machine Learning at Scale
Alexey Kurakin
Ian Goodfellow
Samy Bengio
AAML
253
2,899
0
04 Nov 2016
1