Improving the Robustness of Unexpected Obstacle Detection Models in Autonomous Driving Systems /Amélioration de la Robustesse des Modèles de Détection d’Obstacles inattendus dans les Systèmes de Conduite Autonome
Stage M2 Contact: isetitra@utc.fr. Autonomous driving systems heavily depend on effective environmental perception, particularly in the area of object detection. Although YOLO (You Only Look Once) models [1][2][3] have established themselves as a standard for real-time object detection due to their balance between accuracy and speed, they show limitations when…
