您当前的位置：
首页 >
文章列表页 >
CORM-YOLO： Pedestrian detection algorithm in low-light conditions for traffic environments
Image Processing | 更新时间：2025-09-08

    • CORM-YOLO： Pedestrian detection algorithm in low-light conditions for traffic environments

    • “In the fields of smart cities and intelligent transportation, the CORM-YOLO algorithm significantly improves pedestrian detection capabilities in low light environments, providing important application value for ensuring job safety.”
    • Chinese Journal of Liquid Crystals and Displays   Vol. 40, Issue 9, Pages: 1369-1380(2025)

    • DOI：10.37188/CJLCD.2025-0104    

      CLC： TP391
    • CSTR：32172.14.CJLCD.2025-0104.    

    • Received：20 May 2025，

      Revised：2025-07-17，

      Published：05 September 2025

    移动端阅览

  • WANG Dong, LUO Yabo, ZHANG Feng, et al. CORM-YOLO： Pedestrian detection algorithm in low-light conditions for traffic environments[J]. Chinese journal of liquid crystals and displays, 2025, 40(9): 1369-1380. DOI： 10.37188/CJLCD.2025-0104. CSTR： 32172.14.CJLCD.2025-0104..

  •  
  •  

0

Views

16

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

Remote sensing scene classification model based on improved ShuffleNetV2 network
FRKDNet： feature refine semantic segmentation network based on knowledge distillation

Related Author

HUANG Sui
XU Huiwen
ZHAO Weichao
LI Ze
JIANG Shi-yi
XU Yang
LI Dan-yang
FAN Run-ze

Related Institution

Hubei Tianwei Automobile Co.， LED
Digital Center， Changchun Institute of Optics， Fine Mechanics and Physics， Chinese Academy of Sciences
College of Big Data and Information Engineering， Guizhou University
Guiyang Aluminum-magnesium Design and Research Institute Co.Ltd.
Changchun Institute of Optics， Fine Mechanicsand Physics， Chinese Academy of Sciences， Digital Center
0