您当前的位置：
首页 >
文章列表页 >
Dense small object vehicle detection in UAV aerial images using improved YOLOX
更新时间：2025-07-22

    • Dense small object vehicle detection in UAV aerial images using improved YOLOX

    • “In the field of drone aerial image detection, researchers have proposed an improved YOLOX network, which effectively improves the accuracy of small target detection, reduces the missed detection rate, and provides reference for multi-target tracking applications of high-altitude vehicles.”
    • Journal of Jilin University(Engineering and Technology Edition)   Vol. 55, Issue 4, Pages: 1307-1318(2025)
    • 作者机构：

      1.重庆交通大学 交通运输学院，重庆 400074

      2.重庆交通大学 山区复杂道路环境“人-车-路”协同与安全重庆市重点实验室，重庆 400074

      3.重庆市交通规划研究院，重庆 400074

    • DOI：10.13229/j.cnki.jdxbgxb.20230779    

      CLC： U491

    • Received：25 July 2023，

      Published：01 April 2025

    移动端阅览

  • ZHANG He-shan,FAN Meng-wei,TAN Xin,et al.Dense small object vehicle detection in UAV aerial images using improved YOLOX[J].Journal of Jilin University(Engineering and Technology Edition),2025,55(04):1307-1318. DOI： 10.13229/j.cnki.jdxbgxb.20230779.

  •  
  •  

0

Views

8

下载量

1

CSCD

Alert me when the article has been cited
提交
Tools
Download
Export Citation
Share
Add to favorites
Add to my album

Related Articles

Heterogeneity analysis of residents’ transfer intentions under transit transfer preferential policy
Image adversarial examples generation based on Diff⁃AdvGAN
Modeling and simulation of freeway heterogeneous traffic flow in connected and autonomous vehicle environment
Agent⁃based behavioral simulation of parking reservation services driven by user satisfaction
Defect recognition of lightweight bridges based on YOLOv5

Related Author

MA Zhuang-lin
BI Yu-ming
ZHOU Bei
DENG Ya-juan
ZHAO Xue
ZHAO Hong
MA Yu-xuan
SONG Fu-rong

Related Institution

School of Transportation Engineering， Chang'an University
BYD Automotive Industry Co.， Ltd.
School of Science， Xi'an Shiyou University
School of Computer and Communication， Lanzhou University of Technology
School of Civil Engineering and Transportation， Northeast Forestry University
0