• KB Bini
• Ayush Shreyas Gayakwad
• Murtaza Shabbir Saherwala
• Adeeba Siddique
• Bibi Mariam

Road sign recognition plays a crucial role in autonomous driving and traffic safety systems. This paper presents a real-time road sign detection system leveraging the YOLOv5 model, trained on the German Traffic Sign Recognition Benchmark (GTSRB) dataset. The model classifies 43 different traffic signs with high accuracy, providing a reliable and efficient solution for real-world applications. The proposed system achieves robust results in real-time detection, making it suitable for integration into advanced driver-assistance systems (ADAS) and autonomous vehicles. Model performance is evaluated using precision-recall curves, confusion matrices, and F1-score curves, demonstrating high recognition accuracy.

YOLO,GTSRB

"Road Sign Recognition using YOLO & GTSRB", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 5, page no.g606-g611, May-2025, Available :http://www.jetir.org/papers/JETIR2505760.pdf

"Road Sign Recognition using YOLO & GTSRB", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 5, page no. ppg606-g611, May-2025, Available at : http://www.jetir.org/papers/JETIR2505760.pdf