Thesis: Detecting Adversaries in DQNs and Computer Vision using Bayesian CNNs
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Updated
Sep 13, 2018 - HTML
Thesis: Detecting Adversaries in DQNs and Computer Vision using Bayesian CNNs
The adversarial sample detection model based on edge noise feature
PyTorch implementation of Targeted Adversarial Perturbations for Monocular Depth Predictions (in NeurIPS 2020)
Felice Antonio Merra's Personal Blog. Follow my research activity! @merrafelice
Paper ACTIVE-ICCV2023
AdvSV stands as the first dataset developed specifically for evaluating Speaker Verification (SV) systems against adversarial attacks. It aims to benchmark the robustness of ASV models in the face of such attacks and offers vital resources for researchers to explore the characteristics of adversarial and replay attacks in this domain.
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