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    • 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)   

      Received:20 January 2023

      Published:07 December 2024

    • DOI: 10.11834/jrs.20243016     

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  • 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.
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相关作者

YANG Chao 西南交通大学 地球科学与工程学院
LIU Chang 西南交通大学 地球科学与工程学院
TANG Tengfeng 西南交通大学 地球科学与工程学院
YE Yuanxin 西南交通大学 地球科学与工程学院
CHEN Jin 北京师范大学 地理科学学部
LIU Tianyu 北京师范大学 地理科学学部
SHI Qian 中山大学 地理科学与规划学院
DONG Jinwei 中国科学院地理科学与资源研究所

相关机构

Faculty of Geosciences and Engineering, Southwest Jiaotong University
Faculty of Geography Science, Beijing Normal University
School of Geography and Planning, Sun Yat-sen University
Institute of Geographic Sciences and Resources, Chinese Academy of Sciences
Aerospace Information Research Institute, Chinese Academy of Sciences
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