App. Res. of Comp. Accepted Paper
Vol. 43, 2026 No. 8

AEG-DETR: road object detection method under adverse weather scenarios

Rao Chenxu1
Kan Xi2
Zhang Yonghong3
1. School of Computer Science Cyber Science and Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, China
2. School of Internet of Things Engineering, Wuxi University, Wuxi Jiangsu 214105, China
3. Nanjing University of Information Science and Technology, Jiangsu Provincial Collaborative Innovation Center for Atmospheric Environment and Equipment Technology, Nanjing 210044, China
DOI: 10.19734/j.issn.1001-3695.2025.10.0486

Abstract

To address the performance degradation of road object detection caused by image degradation under severe weather conditions (e. g. , rain and fog) , this study proposed an enhanced RT-DETR-R18 algorithm named AEG-DETR with higher robustness. AEG-DETR designed a cross-stage context-aware dynamic hybrid module (CSP-CADM) to improve environmental adaptability in complex scenarios. A parallel weather-adaptive edge pyramid generator (WA-EPG) dynamically enhanced critical edges while suppressing random noise, thereby strengthening structural perception of blurred or partially occluded targets. The decoder incorporated an adaptive sparse attention module (AIFI-ASSA) to precisely model long-range dependencies with reduced computational overhead. AEG-DETR results on severe weather datasets demonstrated a 4.53% precision improvement, 3.01% recall gain, and 3.58% mAP50 increase over the baseline model, along with 16.7% fewer parameters. The proposed algorithm also achieved 3.82% higher accuracy on the ACDC dataset compared to the original model, outperforming existing methods and validating strong generalization capability. This work achieves state-of-the-art detection accuracy under adverse conditions while maintaining compact model size.

Foundation Support

国家自然科学基金资助项目(42175157,42305158)
江苏省无锡市"太湖之光"科技攻关计划(基础研究)项目(K20231021)
江苏省高等学校基础科学(自然科学)研究面上项目(23KJB170025)
"唐鹤千优秀青年奖"资助项目(2025thq001)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2025.10.0486
Publish at: Application Research of Computers Accepted Paper, Vol. 43, 2026 No. 8

Publish History

[2026-04-09] Accepted Paper

Cite This Article

饶晨旭, 阚希, 张永宏. AEG-DETR:面向恶劣天气下的道路目标检测算法 [J]. 计算机应用研究, 2026, 43 (8). (2026-04-30). https://doi.org/10.19734/j.issn.1001-3695.2025.10.0486. (Rao Chenxu, Kan Xi, Zhang Yonghong. AEG-DETR: road object detection method under adverse weather scenarios [J]. Application Research of Computers, 2026, 43 (8). (2026-04-30). https://doi.org/10.19734/j.issn.1001-3695.2025.10.0486. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

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