您当前的位置：
首页 >
文章列表页 >
Research on Vehicle and Pedestrian Detection Algorithm Based on YOLOv8 in Foggy Environment
Topic: Key Technologies and Applications of Internet of Vehicles | 更新时间：2025-12-16

    • Research on Vehicle and Pedestrian Detection Algorithm Based on YOLOv8 in Foggy Environment

    • “In the field of autonomous driving, researchers have proposed the PF-YOLOv8-AL algorithm, which effectively improves the accuracy of target detection in foggy environments, with an average accuracy value of 82.2%.”
    • Software Guide   Vol. 24, Issue 12, Pages: 18-24(2025)

    • DOI：10.11907/rjdk.241766    

      CLC： TP391.41

    • Received：30 September 2024，

      Published：15 December 2025

    移动端阅览

  • DU Yuting,HE Jia.Research on Vehicle and Pedestrian Detection Algorithm Based on YOLOv8 in Foggy Environment[J].Software Guide,2025,24(12):18-24. DOI： 10.11907/rjdk.241766.

  •  
  •  

0

Views

0

下载量

0

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

Lightweight Nighttime Pedestrian Vehicle Detection Based on RHUS-YOLOv8
Ladder Detection and Positioning Based on Improved YOLOv8
Surface Defect Detection Algorithm of Butyl Rubber Stoppers Based on Improved YOLOv8
Lightweight Detection Algorithm for Tibetan Medicinal Plants Based on Improved YOLOv8

Related Author

ZHANG Yuting
YANG Guang
ZOU Li
WANG Xiaojun
WANG Zidong
PENG Liangliang
XUE Wei
WU Fan

Related Institution

Dalian Key Laboratory of Blockchain Technology and Application
Liaoning Key Laboratory of Welding and Reliability of Rail Transportation Equipment
School of Railway Intelligent Engineering of Dalian Jiaotong University
National Pharmaceutical Group Weiqida Pharmaceutical Co. ， Ltd.
School of Information Science and Engineering， Hebei University of Science and Technology
0