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
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.
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
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