18 citations · 39 across the 6 of their papers we have counts for
6 papers
A Real-Time Generalized Nash Equilibrium Framework for Interaction-Aware Autonomous Driving in Mixed Traffic
Nouhed Naidja, Mohamed-Cherif Rahal, Steve Pechberti +3
Safe and efficient navigation in mixed-traffic environments remains a critical challenge for Autonomous Vehicles (AVs), primarily due to the complex interdependence between the AV'…
Generating Relevant Counter-Examples from a Positive Unlabeled Dataset for Image Classification
Florent Chiaroni, Ghazaleh Khodabandelou, Mohamed-Cherif Rahal +2
With surge of available but unlabeled data, Positive Unlabeled (PU) learning is becoming a thriving challenge. This work deals with this demanding task for which recent GAN-based P…
Self-supervised classification of dynamic obstacles using the temporal information provided by videos
Sid Ali Hamideche, Florent Chiaroni, Mohamed-Cherif Rahal
Nowadays, autonomous driving systems can detect, segment, and classify the surrounding obstacles using a monocular camera. However, state-of-the-art methods solving these tasks gen…
Self-supervised learning for autonomous vehicles perception: A conciliation between analytical and learning methods
Florent Chiaroni, Mohamed-Cherif Rahal, Nicolas Hueber +1
Nowadays, supervised deep learning techniques yield the best state-of-the-art prediction performances for a wide variety of computer vision tasks. However, such supervised techniqu…
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…