Please use this identifier to cite or link to this item:
http://hdl.handle.net/123456789/4936
DC Field | Value | Language |
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dc.contributor.author | Al-Haimi, H. A. | en_US |
dc.contributor.author | Sani, Z. M. | en_US |
dc.contributor.author | Izzudin, T. A. | en_US |
dc.contributor.author | Ab Ghani, H. | en_US |
dc.contributor.author | Azizan, A. | en_US |
dc.contributor.author | Karim, S. A. A. | en_US |
dc.date.accessioned | 2023-10-16T02:38:15Z | - |
dc.date.available | 2023-10-16T02:38:15Z | - |
dc.date.issued | 2023 | - |
dc.identifier.issn | 20894872 | - |
dc.identifier.uri | http://hdl.handle.net/123456789/4936 | - |
dc.description | Scopus | en_US |
dc.description.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. | en_US |
dc.language.iso | en | en_US |
dc.publisher | Institute of Advanced Engineering and Science | en_US |
dc.relation.ispartof | IAES International Journal of Artificial Intelligence (IJ-AI) | en_US |
dc.subject | Deep learning | en_US |
dc.subject | Detection and recognition | en_US |
dc.subject | Traffic counter | en_US |
dc.subject | Traffic light | en_US |
dc.subject | You only look once | en_US |
dc.title | Traffic light counter detection comparison using you only look oncev3 and you only look oncev5 for version 3 and 5 | en_US |
dc.type | International | en_US |
dc.identifier.doi | 10.11591/ijai.v12.i4.pp1585-1592 | - |
dc.description.funding | Universiti Teknikal Malaysia Melaka (UTeM) through Facilitation Research Program by Research & Innovation Management (CRIM). | en_US |
dc.description.page | 1585-1592 | en_US |
dc.description.researcharea | Computer vision | en_US |
dc.volume | 12(4) | en_US |
dc.description.type | Article | en_US |
item.languageiso639-1 | en | - |
item.openairetype | International | - |
item.grantfulltext | open | - |
item.fulltext | With Fulltext | - |
crisitem.author.dept | UNIVERSITI MALAYSIA KELANTAN | - |
Appears in Collections: | Faculty of Data Science and Computing - Journal (Scopus/WOS) |
Files in This Item:
File | Description | Size | Format | |
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22600-45739-2-PB.pdf | Traffic light counter detection comparison using you only look oncev3 and you only look oncev5 for version 3 and 5 | 466.4 kB | Adobe PDF | View/Open |
scopusresults-Traffic light counter detection.pdf | 63.54 kB | Adobe PDF | View/Open |
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