Detection by Attack: Detecting Adversarial Samples by Undercover Attack
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Updated
Feb 13, 2021 - Python
Detection by Attack: Detecting Adversarial Samples by Undercover Attack
Code for "BayesAdapter: Being Bayesian, Inexpensively and Robustly, via Bayeisan Fine-tuning"
Adversarial detection and defense for deep learning systems using robust feature alignment
Adversarial Detection v.s. Object Detection.
A Man-in-the-Middle Attack against Object Detection.
Adversarial Detection in ROS Gazebo.
Gaussian process regression-based adversarial image detection
Using Gaussian Processes for Deep Neural Network Predictive Uncertainty Estimation
An University Project for the AI4Cybersecurity class.
This work demonstrates an altogether different utility of attention heads. Self-attention heads are characteristic of Transformer models and have been well studied for interpretability and pruning, but here we build a novel adversarial detection model based on them.
CSL7360 Course Project Repository
This work demonstrates an altogether different utility of attention heads. Self-attention heads are characteristic of Transformer models and have been well studied for interpretability and pruning, but here we build a novel adversarial detection model based on them.
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