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Traffic light counter detection comparison using you only look oncev3 and you only look oncev5 for version 3 and 5

Al-Haimi, Hamzah Abdulmalek and Md. Sani, Zamani and Ahmad Izzudin, Tarmizi and Abdul Ghani, Hadhrami and Azizan, Azizul and Abdul Karim, Samsul Ariffin (2023) Traffic light counter detection comparison using you only look oncev3 and you only look oncev5 for version 3 and 5. IAES International Journal of Artificial Intelligence, 12 (4). pp. 1585-1592. ISSN 2089-4872

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Official URL: http://dx.doi.org/10.11591/ijai.v12.i4.pp1585-1592

Abstract

This project aims to develop a vision system that can detect traffic light counter and to recognise the numbers shown on it. The system used you only look once version 3 (YOLOv3) algorithm because of its robust performance and reliability and able to be implemented in Nvidia Jetson nano kit. A total of 2204 images consisting of numbers from 0-9 green and 0-9 red. Another 80% (1764) from the images are used for training and 20% (440) are used for testing. The results obtained from the training demonstrated Total precision=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 YOLOv5 algorithm, and the results are substantially close to each other as the YOLOv5 accuracy and recall at 97.5% and 97.5% respectively.

Item Type:Article
Uncontrolled Keywords:Deep learning, Detection and recognition, Traffic counter, Traffic light, You only look once
Subjects:T Technology > T Technology (General)
Divisions:Razak School of Engineering and Advanced Technology
ID Code:107585
Deposited By: Widya Wahid
Deposited On:25 Sep 2024 06:21
Last Modified:25 Sep 2024 06:21

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