您当前的位置:
首页 >
文章列表页 >
Semantic segmentation of aerial images based on multi-scale feature interaction and fusion
Information Sciences | 更新时间:2026-01-29
    • Semantic segmentation of aerial images based on multi-scale feature interaction and fusion

    • In the field of aerial image semantic segmentation, experts have proposed cross level interaction and orientation aware networks, which effectively improve segmentation accuracy and generalization ability.
    • Optics and Precision Engineering   Vol. 34, Issue 2, Pages: 267-279(2026)
    • DOI:10.37188/OPE.20263402.0267    

      CLC: TP394.1;TH691.9
    • CSTR:32169.14.OPE.20263402.0267    
    • Received:20 August 2025

      Revised:2025-09-17

      Published:25 January 2026

    移动端阅览

  • LIU Jie,WU Ziyu,TIAN Ming,et al.Semantic segmentation of aerial images based on multi-scale feature interaction and fusion[J].Optics and Precision Engineering,2026,34(02):267-279.

  •  
  •  

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

Real-time image semantic segmentation based on three-branch network
Weakly supervised image semantic segmentation network driven by spatio-temporal contrastive learning
Urban road semantic segmentation with global awareness and multi-scale feature fusion
Inverse perspective mapping of pavement image combining semantic and 3D information
Multi-scale context-aware network for road extraction in remote sensing images

Related Author

REN Fenglei
GAO Ziyang
ZHANG Yan
ZHOU Haibo
YANG Lu
QIN Zhichang
LIANG Zhen
HU Yanzhu

Related Institution

National Demonstration Center for Experimental Mechanical and Electrical Engineering Education,Tianjin University of Technology
Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control, Tianjin University of Technology
Key Laboratory of IoT Monitoring and Early Warning, Ministry of Emergency Management, Beijing University of Posts and Telecommunications
School of Intelligent Engineering and Automation, Beijing University of Posts and Telecommunications
Pratacultural College, Inner Mongolia Minzu University
0