Traffic light counter detection comparison using you only look oncev3 and you only look oncev5 for version 3 and 5 - Hamzah Abdulmalek Al-Haimi; Zamani Md Sani; Tarmizi Ahmad Izzudin; Hadhrami Abdul Ghani; Azizul Azizan; Samsul Ariffin Abdul Karim (Institute of Advanced Engineering and Science, 2023)
This project aims to develop a vision system that can detect traffic lightcounter and to recognise the numbers shown on it. The system used you onlylook once version 3 (YOLOv3) algorithm because of its robust performanceand reliability and able to be implemented in Nvidia Jetson nano kit. A totalof 2204 images consisting of numbers from 0-9 green and 0-9 red. Another80% (1764) from the images are used for training and 20% (440) are used fortesting. The results obtained from the training demonstrated Totalprecision=89%, Recall=99.2%, F1 score=70%, intersection over union(IoU)=70.49%, mean average precision (mAp)=87.89%, Accuracy=99.2%and the estimate total confidence rate for red and green are 98.4% and 99.3%respectively. The results were compared with the previous YOLOv5algorithm, and the results are substantially close to each other as the YOLOv5accuracy and recall at 97.5% and 97.5% respectively.