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DOI: 10.14569/IJACSA.2022.01309100
PDF

Performance Analysis of Deep Learning YOLO models for South Asian Regional Vehicle Recognition

Author 1: Minar Mahmud Rafi
Author 2: Siddharth Chakma
Author 3: Asif Mahmud
Author 4: Raj Xavier Rozario
Author 5: Rukon Uddin Munna
Author 6: Md. Abrar Abedin Wohra
Author 7: Rakibul Haque Joy
Author 8: Khan Raqib Mahmud
Author 9: Bijan Paul

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 13 Issue 9, 2022.

  • Abstract and Keywords
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Abstract: For years, humans have pondered the possibility of combining human and machine intelligence. The purpose of this research is to recognize vehicles from media and while there are multiple models associated with this, models that can detect vehicles commonly used in developing countries like Bangladesh, India, etc. are scarce. Our focus was to assimilate the largest dataset of vehicles exclusive to South Asia in addition to the more common universal vehicles and apply it to track and recognize these vehicles, even in motion. To develop this, we increased the class variations and quantity of the data and used multiple variations of the YOLOv5 model. We trained different versions of the model with our dataset to properly measure the degree of accuracy between the models in detecting the more unique vehicles. If vehicle detection and tracking are adopted and implemented in live traffic camera feeds, the information can be used to create smart traffic systems that can regulate congestion and routing by identifying and separating fast and slow-moving vehicles on the road. The comparison between the three different YOLOv5 models led to an analysis that indicates that the large variant of the YOLOv5 architecture outperforms the rest.

Keywords: You Only Look Once (YOLOv5); vehicle detection; neural network; deep learning; vehicle tracking

Minar Mahmud Rafi, Siddharth Chakma, Asif Mahmud, Raj Xavier Rozario, Rukon Uddin Munna, Md. Abrar Abedin Wohra, Rakibul Haque Joy, Khan Raqib Mahmud and Bijan Paul, “Performance Analysis of Deep Learning YOLO models for South Asian Regional Vehicle Recognition” International Journal of Advanced Computer Science and Applications(IJACSA), 13(9), 2022. http://dx.doi.org/10.14569/IJACSA.2022.01309100

@article{Rafi2022,
title = {Performance Analysis of Deep Learning YOLO models for South Asian Regional Vehicle Recognition},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2022.01309100},
url = {http://dx.doi.org/10.14569/IJACSA.2022.01309100},
year = {2022},
publisher = {The Science and Information Organization},
volume = {13},
number = {9},
author = {Minar Mahmud Rafi and Siddharth Chakma and Asif Mahmud and Raj Xavier Rozario and Rukon Uddin Munna and Md. Abrar Abedin Wohra and Rakibul Haque Joy and Khan Raqib Mahmud and Bijan Paul}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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