您当前的位置：
首页 >
文章列表页 >
Optical remote sensing road extraction network with directional guidance and topological awareness
Information Sciences | 更新时间：2025-07-08

    • Optical remote sensing road extraction network with directional guidance and topological awareness

    • “In the field of optical remote sensing image road extraction, researchers have proposed a direction guided and topology aware road extraction network, which effectively improves the accuracy and completeness of road extraction.”
    • Optics and Precision Engineering   Vol. 33, Issue 10, Pages: 1638-1656(2025)

    • DOI：10.37188/OPE.20253310.1638    

      CLC： TP394.1;TH691.9
    • CSTR：32169.14.OPE.20253310.1638    

    • Received：10 November 2024，

      Revised：12 January 2025，

      Published：25 May 2025

    移动端阅览

  • MENG Yuebo,HUANG Xinyu,SU Shilong,et al.Optical remote sensing road extraction network with directional guidance and topological awareness[J].Optics and Precision Engineering,2025,33(10):1638-1656. DOI： 10.37188/OPE.20253310.1638. CSTR： 32169.14.OPE.20253310.1638.

  •  
  •  

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

Multi-scale context-aware network for road extraction in remote sensing images
Optical remote sensing road extraction network based on GCN guided model viewpoint
Road extraction technology based on multi-source remote sensing data： review and prospects
Road extraction from high-resolution remote sensing imagery based on local adaptive directional template match

Related Author

JIE Jun
ZHANG Jie
DONG Wei
LI Changhua
HUI Aiting
LI Zhijie
SHAN Zhe
XU Shengjun

Related Institution

School of Information and Control Engineering， Xi’an University of Architectural Science and Technology
Xi'an Key Laboratory of Intelligent Technology for Building and Manufacturing
Center for Geo-Spatial Information， Shenzhen Institute of Advanced Technology， Chinese Academy of Sciences
Key Laboratory of Intelligent Infrared Perception， Shanghai Institute of Technical Physics， Chinese Academy of Sciences
Department of Photogrammetry and Remote Sensing， Finnish Geospatial Research Institute， Krikkonummi FI
0