REFERENCES

1. Wang J, Zhang L, Luo G, Zhang T, Jiang Z. Machine vision applied for laser processing system. Appl Laser 2009;29:523. Available from: https://www.opticsjournal.net/Articles/OJ22833ea80a2c84ab/References#art-nav. [Last accessed on 27 Nov 2024].

2. Zhang W, Xiao Z, Yan Z. Design of online laser marking system by vision guided based on template matching. J Phys Conf Ser 2021;1976:012047.

3. Gao C, Cai Q, Ming S. YOLOv4 object detection algorithm with efficient channel attention mechanism. In: 2020 5th International Conference on Mechanical, Control and Computer Engineering (ICMCCE); 2020 Dec 25-27; Harbin, China. IEEE; 2020. pp. 1764-70.

4. Girshick R, Donahue J, Darrell T, Malik J. Rich feature hierarchies for accurate object detection and semantic segmentation. In: 2014 IEEE Conference on Computer Vision and Pattern Recognition; 2014 Jun 23-28; Columbus, USA. IEEE; 2014. pp. 580-7.

5. Wang S, Yang N, Duan L, Liu L, Dong J. Small-size pedestrian detection in large scene based on fast R-CNN. In: 9th International Conference on Graphic and Image Processing (ICGIP); Qingdao, China. 2017.

6. Liu B, Zhao W, Sun Q. Study of object detection based on faster R-CNN. In: 2017 Chinese Automation Congress (CAC); 2017 Oct 20-22; Jinan, China. IEEE; 2017. pp. 6233-6.

7. Yayla R, Albayrak E, Yüzgeç U. Vehicle detection from unmanned aerial images with deep mask R-CNN. Comput Sci J Moldova 2022;30:148-69.

8. Zhao Q, Wei H, Zhai X. Improving tire specification character recognition in the YOLOv5 network. Appl Sci 2023;13:7310.

9. Arifando R, Eto S, Wada C. Improved YOLOv5-based lightweight object detection algorithm for people with visual impairment to detect buses. Appl Sci 2023;13:5802.

10. Wang H, Zhang X, Guo Y, Li W. Recognition of characters on tire rubber surface based on machine vision. J Electron Meas Instrum 2021;35:191-9.

11. Kazmi W, Nabney I, Vogiatzis G, Rose P, Codd A. An efficient industrial system for vehicle tyre (tire) detection and text recognition using deep learning. IEEE Trans Intell Transp Syst 2021;22:1267-75.

12. Chen Y, Xia Q, Wang J, Zhang W. Control system for laser marking tires with machine vision. Appl Laser 2010;30:191-9.

13. Zheng L, Lou H, Xu X, Lu J. Tire defect detection via 3D laser scanning technology. Appl Sci 2023;13:11350.

14. Chen X, Ma H, Wan J, Li B, Xia T. Multi-view 3D object detection network for autonomous driving. In: 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR); 2017 Jul 21-26; Honolulu, USA. IEEE; 2017. pp. 6526-34.

15. Ku J, Mozifian M, Lee J, Harakeh A, Waslander SL. Joint 3D proposal generation and object detection from view aggregation. In: 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS); 2018 Oct 01-05; Madrid, Spain. IEEE; 2018. p. 1-8.

16. Qi CR, Liu W, Wu C, Su H, Guibas LJ. Frustum pointNets for 3D object detection from RGB-D data. In: 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition; 2018 Jun 18-23; Salt Lake City, USA. IEEE; 2018. pp. 918-27.

17. Xie D, Xu Y, Lu F, Pan S. Real-time detection of 3D objects based on multi-sensor information fusion. Automot Eng 2022;44:340-9.

18. Wu Q, Li L. 3D object detection based on point cloud bird's eye view remapping. J South China Univ Technol 2021;49:39-46.

19. Zhang K, Chen R, Peng Z, Zhu Y, Wang X. FGCN: image-fused point cloud semantic segmentation with fusion graph convolutional network. Sensors 2023;23:8338.

20. Li X, Li Y. Research on the role of multi-sensor system information fusion in improving hardware control accuracy of intelligent system. Nonlinear Eng 2024;13:20240035.

21. Xue Y, Mou S, Chen C, et al. Rapid distance estimation of odor sources by electronic nose with multi-sensor fusion based on spiking neural network. Sensor Actuat B Chem 2025;422:136665.

22. Wang S, Yi S, Zhao B, et al. Sowing depth monitoring system for high-speed precision planters based on multi-sensor data fusion. Sensors 2024;24:6331.

23. Chen L, Moon SK. In-situ defect detection in laser-directed energy deposition with machine learning and multi-sensor fusion. J Mech Sci Technol 2024;38:4477-84.

24. Zhang Z. Flexible camera calibration by viewing a plane from unknown orientations. In: Proceedings of the Seventh IEEE International Conference on Computer Vision; 1999 Sep 20-27; Kerkyra, Greece. IEEE; 1999. pp. 666-73.

25. Zhang Q, He X, Yao S, Guo Z. Research on the fusion technology of camera and lidar based on ROS intelligent mobile robot. China Meas Test 2021;47:120-3. Available from: http://61.54.243.197:8089/KCMS/detail/detail.aspx?filename=SYCS202112019&dbcode=CJFQ&dbname=CJFD2021 [Last accessed on 27 Nov 2024].