Models and Methods | Views : 0 下载量: 274 CSCD: 0
  • Export

  • Share

  • Collection

  • Album

    • Dual-task model for ground crack detection in the goaf of coal mines

    • In the field of surface crack recognition in mining areas, experts have designed a Goaf DTNet dual task convolutional neural network to improve crack detection accuracy through information complementarity, providing effective data for mining area monitoring.
    • Vol. 28, Issue 12, Pages: 3271-3286(2024)   

      Published: 07 December 2024

    • DOI: 10.11834/jrs.20243016     

    移动端阅览

  • Chen X M,Yao X,Ren K Y,Yao C C,Zhou Z K and Yang Y L. 2024. Dual-task model for ground crack detection in the goaf of coal mines. National Remote Sensing Bulletin, 28(12):3271-3286 DOI: 10.11834/jrs.20243016.
  •  
  •  
Alert me when the article has been cited
提交

相关作者

SHAO Pan 三峡大学 湖北省水电工程智能视觉监测重点实验室;三峡大学 计算机与信息学院
GAO Ziang 三峡大学 湖北省水电工程智能视觉监测重点实验室;三峡大学 计算机与信息学院
LEI Xiangda 南京信息工程大学 遥感与测绘工程学院
GUAN Haiyan 南京信息工程大学 遥感与测绘工程学院
DONG Zhen 武汉大学 测绘遥感信息工程国家重点实验室
FANG Tingting 中国科学技术大学 网络空间安全学院;中国科学院电磁空间信息重点实验室
LIU Bin 中国科学技术大学 网络空间安全学院;中国科学院电磁空间信息重点实验室
CHEN Chunhui 安徽省基础测绘信息中心;自然资源部江淮耕地资源保护与生态修复重点实验室

相关机构

Hubei Key Laboratory of Intelligent Vision Monitoring for Hydroelectric Engineering, China Three Gorges University
College of Computer and Information Technology, China Three Gores University
School of Remote Sensing and Geomatics Engineering, Nanjing University of Information Science and Technology
State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing, Wuhan University
School of Cyber Science and Technology, University of Science and Technology of China
0