Have a personal or library account? Click to login
Research on Vehicle and Pedestrian Detection Based on Improved RT-DETR Cover

Research on Vehicle and Pedestrian Detection Based on Improved RT-DETR

By: Jingshu LI and  Jianguo Wang  
Open Access
|Jun 2025

References

  1. Hidayatullah, P.; Syakrani, N.; Sholahuddin, M. R.; Gelar, T.; Tubagus, R. YOLOv8 to YOLOv11: A Comprehensive Architecture In-Depth Comparative Review.
  2. Zhang, X.; Zhang, Y.; Gao, T.; Fang, Y.; Chen, T. A Novel SSD-Based Detection Algorithm Suitable for Small Object. IEICE Trans. Inf. Syst. 2023, E106.D (5), 625–634.
  3. Lin, T.-Y.; Goyal, P.; Girshick, R.; He, K.; Dollar, P. Focal Loss for Dense Object Detection. IEEE Trans. Pattern Anal. Mach. Intell. 2020, 42 (2), 318–327.
  4. Arora, N.; Kumar, Y.; Karkra, R.; Kumar, M. Automatic Vehicle Detection System in Different Environment Conditions Using Fast R-CNN. Multimed. Tools Appl. 2022, 81 (13), 18715–18735.
  5. Abd Alaziz, H. M.; Elmannai, H.; Saleh, H.; Hadjouni, M.; Anter, A. M.; Koura, A.; Kayed, M. Enhancing Fashion Classification with Vision Transformer (ViT) and Developing Recommendation Fashion Systems Using DINOVA2. Electronics 2023, 12 (20), 4263.
  6. Fahad, I. A.; Arean, A. I. H.; Ahmed, N. S.; Hasan, M. Automatic Vehicle Detection Using DETR:A Transformer-Based Approach for Navigating Treacherous Roads. arXiv February 25, 2025.
  7. Cheng Xinmiao, Zhang Xuesong, Cao Bingjie, Song Cunli Research on Improving the Small Object Detection Method of RT-DETR [J]. Computer Engineering and Applications, 1-21.
  8. Azimjonov, J.; Özmen, A. A Real-Time Vehicle Detection and a Novel Vehicle Tracking Systems for Estimating and Monitoring Traffic Flow on Highways. Adv. Eng. Inform. 2021, 50, 101393.
  9. Ghosh, R. On-Road Vehicle Detection in Varying Weather Conditions Using Faster R-CNN with Several Region Proposal Networks. Multimed. Tools Appl. 2021, 80 (17), 25985–25999.
  10. Wu, T.; Li, X.; Dong, Q. An Improved Transformer-Based Model for Urban Pedestrian Detection. Int. J. Comput. Intell. Syst. 2025, 18 (1), 68.
  11. Xing, Y.; Yang, S.; Wang, S.; Zhang, S.; Liang, G.; Zhang, X.; Zhang, Y. MS-DETR: Multispectral Pedestrian Detection Transformer with Loosely Coupled Fusion and Modality-Balanced Optimization. IEEE Trans. Intell. Transp. Syst. 2024, 25 (12), 20628–20642.
  12. Song, Y.; Qian, P.; Zhang, K.; Liu, S.; Zhai, R.; Song, R. An Improved Multi-Scale Fusion and Small Object Enhancement Method for Efficient Pedestrian Detection in Dense Scenes. Multimed. Syst. 2025, 31 (2), 151.
  13. Sadik, M. N.; Hossain, T.; Sayeed, F. Real-Time Detection and Analysis of Vehicles and Pedestrians Using Deep Learning. arXiv April 11, 2024.
  14. Zhao, Y.; Lv, W.; Xu, S.; Wei, J.; Wang, G.; Dang, Q.; Liu, Y.; Chen, J. DETRs Beat YOLOs on Real-Time Object Detection. arXiv April 3, 2024.
  15. Xu, Y.; Du, W.; Deng, L.; Zhang, Y.; Wen, W. Ship Target Detection in SAR Images Based on SimAM Attention YOLOv8. IET Commun. 2024, 18 (19), 1428–1436.
Language: English
Page range: 85 - 93
Published on: Jun 16, 2025
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year

© 2025 Jingshu LI, Jianguo Wang, published by Xi’an Technological University
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.