Who Cited It

Universal Adversarial Perturbations

2017 · 2,744 citations · 9 from inside this corpus

Seyed-Mohsen Moosavi-Dezfooli, Alhussein Fawzi, Omar Fawzi, Pascal Frossard

The source holds an abstract for this work, but its best open-access copy is under no open licence, which does not permit us to republish the text. Read it at the source below.

Universal Adversarial Perturbations (2017)Universal Adversarial Perturb…Explaining and Harnessing Adversarial Examples (2014)Explaining and Harnessing Adv…Intriguing properties of neural networks (2013)Intriguing properties of neur…DeepFool: A Simple and Accurate Method to Fool Deep Neural Networks (2016)DeepFool: A Simple and Accura…Boosting Adversarial Attacks with Momentum (2018)Boosting Adversarial Attacks …Explainable AI: A Review of Machine Learning Interpretability Methods (2020)Explainable AI: A Review of M…Robust Physical-World Attacks on Deep Learning Visual Classification (2018)Robust Physical-World Attacks…Threat of Adversarial Attacks on Deep Learning in Computer Vision: A Survey (2018)Threat of Adversarial Attacks…Feature Squeezing: Detecting Adversarial Examples in Deep Neural Networks (2018)Feature Squeezing: Detecting …Adversarial Examples: Attacks and Defenses for Deep Learning (2019)Adversarial Examples: Attacks…ZOO (2017)ZOOOne Pixel Attack for Fooling Deep Neural Networks (2019)One Pixel Attack for Fooling …Neural Cleanse: Identifying and Mitigating Backdoor Attacks in Neural Networks (2019)Neural Cleanse: Identifying a…
12 of 12 neighbouring works in this corpus. Blue is what this paper cites; orange is what cites it, and a dashed line is one neighbour citing another. Only the largest labels are drawn — every node carries its full title on hover.
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What this paper cites, inside the corpus

PaperYearCited
Explaining and Harnessing Adversarial Examples20148,146
Intriguing properties of neural networks20135,739
DeepFool: A Simple and Accurate Method to Fool Deep Neural Networks20165,392

What cites it, inside the corpus

PaperYearCited
Boosting Adversarial Attacks with Momentum20183,040
Explainable AI: A Review of Machine Learning Interpretability Methods20202,907
Robust Physical-World Attacks on Deep Learning Visual Classification20182,154
Threat of Adversarial Attacks on Deep Learning in Computer Vision: A Survey20182,090
Feature Squeezing: Detecting Adversarial Examples in Deep Neural Networks20181,882
Adversarial Examples: Attacks and Defenses for Deep Learning20191,786
ZOO20171,779
One Pixel Attack for Fooling Deep Neural Networks20191,715
Neural Cleanse: Identifying and Mitigating Backdoor Attacks in Neural Networks20191,404

Links

DOI · Open access copy · OpenAlex record

Topics

Adversarial Robustness in Machine LearningComputer Science
Anomaly Detection Techniques and ApplicationsComputer Science
Advanced Neural Network ApplicationsComputer Science

Is this record sound?

complete

Nothing in this record contradicts itself and no field we check is missing.

  • supports4 author record(s) attached.
  • supports37 reference(s) recorded.
  • supportsThe DOI's year agrees with the publication year.
  • supportsA title is present.

Provenance

Everything above was read from one stored OpenAlex payload, fetched 2026-09-04T03:58:48+00:00.

sha256 46f669157f96ea35…