Benchmarking Safety Monitors for Image Classifiers with Machine Learning

4 October 2021

Papers citing "Benchmarking Safety Monitors for Image Classifiers with Machine Learning"

11 / 11 papers shown

Title
Enhancing System Self-Awareness and Trust of AI: A Case Study in Trajectory Prediction and Planning Lars Ullrich Zurab Mujirishvili Knut Graichen 54 0 0 25 Apr 2025
Attention Masks Help Adversarial Attacks to Bypass Safety Detectors Yunfan Shi AAML 32 0 0 07 Nov 2024
Online Safety Analysis for LLMs: a Benchmark, an Assessment, and a Path Forward Xuan Xie Jiayang Song Zhehua Zhou Yuheng Huang Da Song Lei Ma OffRL 37 6 0 12 Apr 2024
SMARLA: A Safety Monitoring Approach for Deep Reinforcement Learning Agents Amirhossein Zolfagharian Manel Abdellatif Lionel C. Briand S. Ramesh 25 5 0 03 Aug 2023
Out-Of-Distribution Detection Is Not All You Need Joris Guérin Kevin Delmas Raul Sena Ferreira Jérémie Guiochet OODD 25 32 0 29 Nov 2022
Unifying Evaluation of Machine Learning Safety Monitors Joris Guérin Raul Sena Ferreira Kevin Delmas Jérémie Guiochet 33 11 0 31 Aug 2022
CheapET-3: Cost-Efficient Use of Remote DNN Models Michael Weiss 23 1 0 24 Aug 2022
Evaluation of Runtime Monitoring for UAV Emergency Landing Joris Guérin Kevin Delmas Jérémie Guiochet 13 13 0 07 Feb 2022
Fail-Safe Execution of Deep Learning based Systems through Uncertainty Monitoring Michael Weiss Paolo Tonella AAML 40 29 0 01 Feb 2021
Adversarial examples in the physical world Alexey Kurakin Ian Goodfellow Samy Bengio SILM AAML 272 5,833 0 08 Jul 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 279 9,136 0 06 Jun 2015