Research of Highway Vehicle Inspection Based on Improved YOLOv5
Author:
Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-99-7025-4_15
Reference21 articles.
1. Hussain, M.M., Beg, M.S.: Using vehicles as fog infrastructures for transportation cyber-physical systems (T-CPS): fog computing for vehicular networks. Int. J. Softw. Sci. Comput. Intell. (IJSSCI) 11(1), 47–69 (2019)
2. Arora, N., Kumar, Y., Karkra, R., Kumar, M.: Automatic vehicle detection system in different environment conditions using fast R-CNN. Multimedia Tools Appl. 81(13), 18715–18735 (2022)
3. Doan, T.N., Truong, M.T.: Real-time vehicle detection and counting based on YOLO and DeepSORT. In: 2020 12th International Conference on Knowledge and Systems Engineering (KSE), pp. 67–72. IEEE (2020)
4. Girshick, R., Donahue, J., Darrell, T., Malik, J.: Rich feature hierarchies for accurate object detection and semantic segmentation. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 580–587 (2014)
5. Girshick, R.: Fast R-CNN. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 1440–1448 (2015)
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