Traffic Sign Recognition

Traffic sign recognition (TSR) aims to enable automated systems, such as autonomous vehicles, to accurately identify and interpret road signs. Current research focuses on improving the robustness of TSR systems against challenging conditions (e.g., adverse weather, variations in sign appearance across regions) and adversarial attacks (e.g., physical stickers or light projections designed to mislead the system), often employing deep learning models like YOLO, Vision Transformers, and Convolutional Neural Networks. These advancements are crucial for enhancing the safety and reliability of autonomous driving and other intelligent transportation systems, contributing significantly to the broader field of computer vision and machine learning.