21 citations · 23 across the 5 of their papers we have counts for
8 papers
Out-Of-Distribution Detection Is Not All You Need
Joris Guérin, Kevin Delmas, Raul Sena Ferreira +1
The usage of deep neural networks in safety-critical systems is limited by our ability to guarantee their correct behavior. Runtime monitors are components aiming to identify unsaf…
Unifying Evaluation of Machine Learning Safety Monitors
Joris Guerin, Raul Sena Ferreira, Kevin Delmas +1
With the increasing use of Machine Learning (ML) in critical autonomous systems, runtime monitors have been developed to detect prediction errors and keep the system in a safe stat…
Evaluation of Runtime Monitoring for UAV Emergency Landing
Joris Guerin, Kevin Delmas, Jérémie Guiochet
To certify UAV operations in populated areas, risk mitigation strategies -- such as Emergency Landing (EL) -- must be in place to account for potential failures. EL aims at reducin…
Benchmarking Safety Monitors for Image Classifiers with Machine Learning
Raul Sena Ferreira, Jean Arlat, Jeremie Guiochet +1
High-accurate machine learning (ML) image classifiers cannot guarantee that they will not fail at operation. Thus, their deployment in safety-critical applications such as autonomo…
Certifying Emergency Landing for Safe Urban UAV
Joris Guerin, Kevin Delmas, Jérémie Guiochet
Unmanned Aerial Vehicles (UAVs) have the potential to be used for many applications in urban environments. However, allowing UAVs to fly above densely populated areas raises concer…
Hazard analysis of human--robot interactions with HAZOP--UML
Jérémie Guiochet
New safety critical systems are about to appear in our everyday life: advanced robots able to interact with humans and perform tasks at home, in hospitals , or at work. A hazardous…