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Vehicle Number Plate Detection and Recognition Using Deep Learning
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[1] M. Bensouilah, M. N. Zennir, and M. Taffar, “An ALPR system-based deep networks for the detection and recognition,” in Proceedings of the 10th International Conference on Pattern Recognition Applications and Methods (ICPRAM), pp. 204-211, 2021.
[2] N. Salsabila and Sriani, “Enhancing automated vehicle license plate recognition with YOLOv8 and EasyOCR,” Journal of Information Systems and Informatics, vol. 6, no. 3, pp. 1577-158x, Sep. 2024.
[3] S. Zhu, Y. Wang, and Z. Wang, “A lightweight license plate detection algorithm based on deep learning,” IET Image Processing, vol. 18, no. 12, pp. 403-411, Oct. 2023.
[4] Z. Ebrahimi Vargoorani, A. M. Ghoreyshi, and Y. Suen, “Efficient License Plate Recognition via Pseudo - Labeled Supervision with Grounding DINO and YOLOv8,” in Proc. IEEE International Workshop on Machine Learning for Signal Processing (MLSP), pp. 1–6, 2025.
[5] M. Tan and Q. V. Le, "EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks," arXiv preprint arXiv:1905.11946, 2019.
[6] R. Laroca, L. A. Zanlorensi, G. R. Gonçalves, E. Todt, W. R. Schwartz, and D. Menotti, “An efficient and layout- independent automatic license plate recognition system based on the YOLO detector,” arXiv:1909.01754 [cs.CV], Sep. 2019.
[7] B. Satya et al., “Optimized automatic license plate recognition for resource-constrained devices,” Eng. Technol. Appl. Sci. Res., vol. 15, no. 2, pp. 21976–21981, Apr. 2025.
[8] L. Zhou, W. Dai, G. Zhang, H. Lou, and J. Yang, “Chinese license plate recognition system design based on YOLOv4 and CRNN + CTC algorithm,” in Proc. 14th EAI Int. Conf. Mobile Multimedia Communications (MOBIMEDIA), Virtual Event, 2021.
[9] B. Satya, D. Manongga, H. and A. Aminuddin, “Optimized YOLOv8 for automatic license plate recognition on resource- constrained devices,” Engineering, Technology & Applied Science Research, vol. 15, no. 2, pp. 21976–21981, Apr. 2025.
[10] E. A. AlQaralleh, F. Aldhaban, H. Nasseif , B. Alqaralleh , and T. AbuKhalil, “Hybrid Metaheuristics Based License Plate Character Recognition in Smart City,” Computers, Materials & Continua, vol. 72, no. 3, pp. 5727–5740, 2022.
Title: Vehicle Number Plate Detection and Recognition Using Deep Learning
Description:
[1] M.
Bensouilah, M.
N.
Zennir, and M.
Taffar, “An ALPR system-based deep networks for the detection and recognition,” in Proceedings of the 10th International Conference on Pattern Recognition Applications and Methods (ICPRAM), pp.
204-211, 2021.
[2] N.
Salsabila and Sriani, “Enhancing automated vehicle license plate recognition with YOLOv8 and EasyOCR,” Journal of Information Systems and Informatics, vol.
6, no.
3, pp.
1577-158x, Sep.
2024.
[3] S.
Zhu, Y.
Wang, and Z.
Wang, “A lightweight license plate detection algorithm based on deep learning,” IET Image Processing, vol.
18, no.
12, pp.
403-411, Oct.
2023.
[4] Z.
Ebrahimi Vargoorani, A.
M.
Ghoreyshi, and Y.
Suen, “Efficient License Plate Recognition via Pseudo - Labeled Supervision with Grounding DINO and YOLOv8,” in Proc.
IEEE International Workshop on Machine Learning for Signal Processing (MLSP), pp.
1–6, 2025.
[5] M.
Tan and Q.
V.
Le, "EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks," arXiv preprint arXiv:1905.
11946, 2019.
[6] R.
Laroca, L.
A.
Zanlorensi, G.
R.
Gonçalves, E.
Todt, W.
R.
Schwartz, and D.
Menotti, “An efficient and layout- independent automatic license plate recognition system based on the YOLO detector,” arXiv:1909.
01754 [cs.
CV], Sep.
2019.
[7] B.
Satya et al.
, “Optimized automatic license plate recognition for resource-constrained devices,” Eng.
Technol.
Appl.
Sci.
Res.
, vol.
15, no.
2, pp.
21976–21981, Apr.
2025.
[8] L.
Zhou, W.
Dai, G.
Zhang, H.
Lou, and J.
Yang, “Chinese license plate recognition system design based on YOLOv4 and CRNN + CTC algorithm,” in Proc.
14th EAI Int.
Conf.
Mobile Multimedia Communications (MOBIMEDIA), Virtual Event, 2021.
[9] B.
Satya, D.
Manongga, H.
and A.
Aminuddin, “Optimized YOLOv8 for automatic license plate recognition on resource- constrained devices,” Engineering, Technology & Applied Science Research, vol.
15, no.
2, pp.
21976–21981, Apr.
2025.
[10] E.
A.
AlQaralleh, F.
Aldhaban, H.
Nasseif , B.
Alqaralleh , and T.
AbuKhalil, “Hybrid Metaheuristics Based License Plate Character Recognition in Smart City,” Computers, Materials & Continua, vol.
72, no.
3, pp.
5727–5740, 2022.
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