Your Location:
Home >
Browse articles >
Road traffic sign recognition algorithm based on improved YOLOv4
Information Sciences | Updated:2026-09-12
    • Road traffic sign recognition algorithm based on improved YOLOv4

    • LI Daxiang , SU Zhongheng , LIU Ying
    • Optics and Precision Engineering Vol. 31, Issue 9, Pages: 1366-1378(2023)
    • DOI: 10.37188/OPE.20233109.1366     

      CLC:
    • Revised:2022-08-08 ,

    Scan QR Code

  •  
  •  
  • Full Text(HTML)

  • Figs( 8 ) Tabs( 4 )

  • References

  • Publication Info

  • Metrics

Sections
icon
The trial reading is over, you can activate your VIP account to continue reading.
Deactivate >
icon
The trial reading is over. You can log in to your account, go to the personal center, purchase VIP membership, and read the full text.
Already a VIP member?
Log in >

743

Views

1541

Downloads

4

CSCD

Alert me when the article has been cited
Submit
Tools
  • BibTeXDownload
  • EndnoteDownload
  • RefMan Download
  • NoteExpressDownload
  • NoteFirstDownload

Related Articles

Real-time deblurring of wideband small target based on attention mechanism
Multi-stage frame alignment video super- resolution network
Multi-scale vehicle and pedestrian detection algorithm based on attention mechanism
Human action recognition based on improved two-stream spatiotemporal network
Dense pedestrian detection algorithm based on multi-scale feature fusion for low-light nighttime scenes

Related Author

ZHU Deyan
AO Yongqi
XU Jiayi
LI Chengcheng
ZHANG Yufan
WANG Sen
ZHU Yang
ZHANG Yinhui

Related Institution

College of Astronautics, Nanjing University of Aeronautics and Astronautics
Key Laboratory of Space Optoelectronic Detection and Perception, Nanjing University of Aeronautics and Astronautics
Faculty of Mechanical and Electrical Engineering,Kunming University of Science and Technology
Institute of Intelligent Machines, Chinese Academy of Sciences
University of Science and Technology of China