1 citations · 1 across the 9 of their papers we have counts for
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Robust Validation to Geometric Perturbations for Autonomous Pose Estimation
Gregoire Theau, Melanie Ducoffe
Deploying autonomous systems in safety-critical domains demands guaranteed robustness against physically plausible geometric perturbations rather than abstract pixel-wise noise. In…
Certified geometric robustness -- Super-DeepG
Noémie Cohen, Mélanie Ducoffe, Christophe Gabreau +2
Safety-critical applications are required to perform as expected in normal operations. Image processing functions are often required to be insensitive to small geometric perturbati…
LARD 2.0: Enhanced Datasets and Benchmarking for Autonomous Landing Systems
Yassine Bougacha, Geoffrey Delhomme, Mélanie Ducoffe +8
This paper addresses key challenges in the development of autonomous landing systems, focusing on dataset limitations for supervised training of Machine Learning (ML) models for ob…
FAME: Formal Abstract Minimal Explanation for Neural Networks
Ryma Boumazouza, Raya Elsaleh, Melanie Ducoffe +2
We propose FAME (Formal Abstract Minimal Explanations), a new class of abductive explanations grounded in abstract interpretation. FAME is the first method to scale to large neural…