您当前的位置：
首页 >
文章列表页 >
Residual network based curve enhanced lane detection method
更新时间：2025-05-26

    • Residual network based curve enhanced lane detection method

    • “In the field of bend detection, researchers have proposed a bend enhanced lane detection method based on residual networks, which effectively improves algorithm performance in bend scenes while reducing model complexity.”
    • Journal of Jilin University(Engineering and Technology Edition)   Vol. 53, Issue 2, Pages: 584-592(2023)
    • 作者机构：

      1.吉林大学 计算机科学与技术学院，长春 130012

      2.吉林大学 符号计算与知识工程教育部重点实验室，长春 130012

      3.吉林大学 机械与航空航天工程学院， 长春 130022

      4.吉林大学 生物与农业工程学院， 长春 130022

      5.吉林大学 工程仿生教育部重点实验室， 长春 130022

    • DOI：10.13229/j.cnki.jdxbgxb20210618    

      CLC： TP391.4

    • Received：05 July 2021，

      Published：01 February 2023

    移动端阅览

  • SHI Xiao-hu,WU Jia-qi,WU Chun-guo,et al.Residual network based curve enhanced lane detection method[J].Journal of Jilin University(Engineering and Technology Edition),2023,53(02):584-592. DOI： 10.13229/j.cnki.jdxbgxb20210618.

  •  
  •  

0

Views

21

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

Method of lane detection based on adaptive fusion of double branch features
Dense small object vehicle detection in UAV aerial images using improved YOLOX
Facial super-resolution reconstruction method based on generative adversarial networks
Voiceprint recognition method based on novel loss function DV-Softmax
Accurate lane detection of complex environment based on double feature extraction network

Related Author

CHEN Yue-tian
YU Yang
XIE Peng-fei
DENG Tian-min
XU Jin
KOU Li-ming
ZHENG Zhan-ji
TAN Xin

Related Institution

School of Traffic and Transportation， Chongqing Jiaotong University
Chongqing Transportation Planning and Research Institute
Chongqing Key Laboratory of "Human-Vehicle-Road" Cooperation and Safety for Mountain Complex Environment， Chongqing Jiaotong University
School of Traffic & Transportation， Chongqing Jiaotong University
School of Computer Science and Artificial Intelligence， Wuhan University of Technology
0