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Helmet and Number Plate Detection Using Deep Learning
Authors
1 Professor, Department of Information Science and Engineering, Bapuji Institution of Engineering and Technology, Davangere, affiliated to VTU Belgavi, Karnataka, India. 2 3 4 5 Bachelor of Engineering, Department of Information Science and Engineering, Bapuji Institution of Engineering and Technology, Davangere, affiliated to VTU Belgavi, Karnataka, India.
Article Information
- DOI
- No DOI
- Published In
- Volume 5, Issue 6 (2025)
- Published Online
- November-December 2025
- Pages
- 16-19
- Article Type
- Original Article
- Check for updates
- No DOI available for cross-reference
References
1. J. Redmon, S. Divvala, R. Girshick, and A. Farhadi, “You Only Look Once: Unified, Real-Time Object Detection,” Proc. CVPR, 2016.
2. J. Redmon and A. Farhadi, “YOLO9000: Better, Faster, Stronger,” Proc. CVPR, 2017.
3. J. Redmon and A. Farhadi, “YOLOv3: An Incremental Improvement,” arXiv: 1804.02767, 2018.
4. A. Bochkovskiy, C. Y. Wang, and H. Y. M. Liao, “YOLOv4: Optimal Speed and Accuracy of Object Detection,” arXiv: 2004.10934, 2020.
5. G. Jocher et al., “YOLOv5,” Ultralytics, 2020. [Online]. Available: https://github.com/ultralytics/yolov5
6. C. Y. Wang et al., “YOLOv7: Trainable Bag-of-Freebies Sets New State-of-the-Art,” arXiv: 2207.02696, 2022.
7. Ultralytics, “YOLOv8: Next-Generation Vision Model,” Ultralytics, 2023. [Online]. Available: https://github.com/ultralytics/ultralytics
8. R. Girshick, “Fast R-CNN,” Proc. ICCV, 2015.
9. S. Ren, K. He, R. Girshick, and J. Sun, “Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks,” TPAMI,
2017.
10. W. Liu et al., “SSD: Single Shot MultiBox Detector,” Proc. ECCV, 2016.
11. M. Everingham et al., “The Pascal Visual Object Classes (VOC) Challenge,” IJCV, 2010.
12. A. Krizhevsky, I. Sutskever, and G. Hinton, “ImageNet Classification with Deep Convolutional Neural Networks,” Proc. NeurIPS, 2012.
13. S. Ioffe and C. Szegedy, “Batch Normalization: Accelerating Deep Network Training,” Proc. ICML, 2015.
14. K. He, X. Zhang, S. Ren, and J. Sun, “Deep Residual Learning for Image Recognition,” Proc. CVPR, 2016.
15. D. Karpathy et al., “Large-Scale Video Classification,” Proc. CVPR, 2014.
16. N. Dalal and B. Triggs, “Histograms of Oriented Gradients for Human Detection,” Proc. CVPR, 2005.
17. R. Smith, “An Overview of the Tesseract OCR Engine,” Proc. ICDAR, 2007.
18. B. Shi, X. Bai, and C. Yao, “An End-to-End Trainable Neural Network for Image-Based Sequence Recognition and Its Application to Scene
Text Recognition,” TPAMI, 2017.
19. S. Bisen and A. Wajgi, “Detection of Motorcycle Riders without Helmet in Traffic Surveillance Video Using Deep Learning,” Proc. ICCCA,
2019.
20. R. Hallavath et al., “Automatic Helmet Detection for Motorcyclists Using Object Detection Models,” Proc. ICICT, 2021.
21. M. P. Anjana and V. Paul, “Helmet Detection System Using CNN for Motorcyclist Safety,” Proc. ICACC, 2020.
22. A. Kumar et al., “Automatic Number Plate Recognition: A Review,” IEEE Access, 2021.
23. S. Du, M. Ibrahim, M. Shehata, and W. Badawy, “Automatic License Plate Recognition (ALPR): A State-of-the-Art Review,” IEEE Trans.
Circuits and Systems for Video Technology, 2013.
24. S. Z. Yussof et al., “Motorcycle Helmet Detection Using Deep Learning,” Proc. ICIT, 2020.
25. P. Gupta and S. A. K. Jilani, “Real-Time Helmet and License Plate Detection Using YOLO and OCR,” Proc. ICICICT, 2022.
2. J. Redmon and A. Farhadi, “YOLO9000: Better, Faster, Stronger,” Proc. CVPR, 2017.
3. J. Redmon and A. Farhadi, “YOLOv3: An Incremental Improvement,” arXiv: 1804.02767, 2018.
4. A. Bochkovskiy, C. Y. Wang, and H. Y. M. Liao, “YOLOv4: Optimal Speed and Accuracy of Object Detection,” arXiv: 2004.10934, 2020.
5. G. Jocher et al., “YOLOv5,” Ultralytics, 2020. [Online]. Available: https://github.com/ultralytics/yolov5
6. C. Y. Wang et al., “YOLOv7: Trainable Bag-of-Freebies Sets New State-of-the-Art,” arXiv: 2207.02696, 2022.
7. Ultralytics, “YOLOv8: Next-Generation Vision Model,” Ultralytics, 2023. [Online]. Available: https://github.com/ultralytics/ultralytics
8. R. Girshick, “Fast R-CNN,” Proc. ICCV, 2015.
9. S. Ren, K. He, R. Girshick, and J. Sun, “Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks,” TPAMI,
2017.
10. W. Liu et al., “SSD: Single Shot MultiBox Detector,” Proc. ECCV, 2016.
11. M. Everingham et al., “The Pascal Visual Object Classes (VOC) Challenge,” IJCV, 2010.
12. A. Krizhevsky, I. Sutskever, and G. Hinton, “ImageNet Classification with Deep Convolutional Neural Networks,” Proc. NeurIPS, 2012.
13. S. Ioffe and C. Szegedy, “Batch Normalization: Accelerating Deep Network Training,” Proc. ICML, 2015.
14. K. He, X. Zhang, S. Ren, and J. Sun, “Deep Residual Learning for Image Recognition,” Proc. CVPR, 2016.
15. D. Karpathy et al., “Large-Scale Video Classification,” Proc. CVPR, 2014.
16. N. Dalal and B. Triggs, “Histograms of Oriented Gradients for Human Detection,” Proc. CVPR, 2005.
17. R. Smith, “An Overview of the Tesseract OCR Engine,” Proc. ICDAR, 2007.
18. B. Shi, X. Bai, and C. Yao, “An End-to-End Trainable Neural Network for Image-Based Sequence Recognition and Its Application to Scene
Text Recognition,” TPAMI, 2017.
19. S. Bisen and A. Wajgi, “Detection of Motorcycle Riders without Helmet in Traffic Surveillance Video Using Deep Learning,” Proc. ICCCA,
2019.
20. R. Hallavath et al., “Automatic Helmet Detection for Motorcyclists Using Object Detection Models,” Proc. ICICT, 2021.
21. M. P. Anjana and V. Paul, “Helmet Detection System Using CNN for Motorcyclist Safety,” Proc. ICACC, 2020.
22. A. Kumar et al., “Automatic Number Plate Recognition: A Review,” IEEE Access, 2021.
23. S. Du, M. Ibrahim, M. Shehata, and W. Badawy, “Automatic License Plate Recognition (ALPR): A State-of-the-Art Review,” IEEE Trans.
Circuits and Systems for Video Technology, 2013.
24. S. Z. Yussof et al., “Motorcycle Helmet Detection Using Deep Learning,” Proc. ICIT, 2020.
25. P. Gupta and S. A. K. Jilani, “Real-Time Helmet and License Plate Detection Using YOLO and OCR,” Proc. ICICICT, 2022.
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