96 citations · 114 across the 2 of their papers we have counts for
7 papers
Probabilistic Jacobian-based Saliency Maps Attacks
Théo Combey, António Loison, Maxime Faucher +1
Neural network classifiers (NNCs) are known to be vulnerable to malicious adversarial perturbations of inputs including those modifying a small fraction of the input features named…
Geomstats: A Python Package for Riemannian Geometry in Machine Learning
Nina Miolane, Alice Le Brigant, Johan Mathe +16
We introduce Geomstats, an open-source Python toolbox for computations and statistics on nonlinear manifolds, such as hyperbolic spaces, spaces of symmetric positive definite matri…
FRSign: A Large-Scale Traffic Light Dataset for Autonomous Trains
Jeanine Harb, Nicolas Rébéna, Raphaël Chosidow +3
In the realm of autonomous transportation, there have been many initiatives for open-sourcing self-driving cars datasets, but much less for alternative methods of transportation su…
From Node Embedding To Community Embedding : A Hyperbolic Approach
Thomas Gerald, Hadi Zaatiti, Hatem Hajri +2
Detecting communities on graphs has received significant interest in recent literature. Current state-of-the-art community embedding approach called \textit{ComE} tackles this prob…
Automatic generation of ground truth for the evaluation of obstacle detection and tracking techniques
Hatem Hajri, Emmanuel Doucet, Marc Revilloud +3
As automated vehicles are getting closer to becoming a reality, it will become mandatory to be able to characterise the performance of their obstacle detection systems. This valida…
Real Time Lidar and Radar High-Level Fusion for Obstacle Detection and Tracking with evaluation on a ground truth
Hatem Hajri, Mohamed-Cherif Rahal
- Both Lidars and Radars are sensors for obstacle detection. While Lidars are very accurate on obstacles positions and less accurate on their velocities, Radars are more precise on…