1 citations · 1 across the 9 of their papers we have counts for
9 papers
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…
Robust Vision-Based Runway Detection through Conformal Prediction and Conformal mAP
Alya Zouzou, Léo andéol, Mélanie Ducoffe +1
We explore the use of conformal prediction to provide statistical uncertainty guarantees for runway detection in vision-based landing systems (VLS). Using fine-tuned YOLOv5 and YOL…
How to design a dataset compliant with an ML-based system ODD?
Cyril Cappi, Noémie Cohen, Mélanie Ducoffe +8
This paper focuses on a Vision-based Landing task and presents the design and the validation of a dataset that would comply with the Operational Design Domain (ODD) of a Machine-Le…
VerifIoU -- Robustness of Object Detection to Perturbations
Noémie Cohen, Mélanie Ducoffe, Ryma Boumazouza +4
We introduce a novel Interval Bound Propagation (IBP) approach for the formal verification of object detection models, specifically targeting the Intersection over Union (IoU) metr…
Robustness Assessment of a Runway Object Classifier for Safe Aircraft Taxiing
Yizhak Elboher, Raya Elsaleh, Omri Isac +6
As deep neural networks (DNNs) are becoming the prominent solution for many computational problems, the aviation industry seeks to explore their potential in alleviating pilot work…
Surrogate Neural Networks Local Stability for Aircraft Predictive Maintenance
Mélanie Ducoffe, Guillaume Povéda, Audrey Galametz +5
Surrogate Neural Networks are nowadays routinely used in industry as substitutes for computationally demanding engineering simulations (e.g., in structural analysis). They allow to…