Views : 0 下载量: 0 CSCD: 0
  • Export

  • Share

  • Collection

  • Album

    • A hybrid method for major food crops leaf chlorophyll content inversion driven by remote sensing mechanisms and deep learning

    • Experts have developed an LCC inversion framework driven by both remote sensing mechanisms and deep learning, providing a universal solution for non-destructive monitoring of LCC in multiple regions and crops.
    • Pages: 1-21(2026)   

      Received:28 May 2025

      Online First:13 March 2026

    • DOI: 10.11834/jrs.20265150     

    移动端阅览

  • SHEN Yanyan,MENG Ran,LI Jiasheng,ZHAO Ping,ZHAO Feng,SUN Rui,ZHANG Hongyan,NI Xiang,LU Lijie,LIU Yong,LIU Jie. XXXX. A hybrid method for major food crops leaf chlorophyll content inversion driven by remote sensing mechanisms and deep learning. National Remote Sensing Bulletin, XX(XX):1-21 DOI: 10.11834/jrs.20265150.
  •  
  •  
Alert me when the article has been cited
提交

相关作者

CHENG Yuhu 中国矿业大学 信息与控制工程学院
KONG Yi 中国矿业大学 信息与控制工程学院
JIANG Wenchao 中国矿业大学 信息与控制工程学院
WANG Xuesong 中国矿业大学 信息与控制工程学院
LIU Qinhuo 中国科学院空天信息创新研究院 遥感科学国家重点实验室;中国科学院大学
GU Chenpeng 中国科学院空天信息创新研究院 遥感科学国家重点实验室;中国科学院大学
LI Jing 中国科学院空天信息创新研究院 遥感科学国家重点实验室;中国科学院大学
ZHANG Hu 中国科学院空天信息创新研究院 遥感科学国家重点实验室;中国科学院大学

相关机构

College of Information and Control Engineering, China University of Mining and Technology
State Key Laboratory of Remote Sensing Science, Jointly Sponsored by Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing Normal University
University of Chinese Academy of Sciences
School of Mechatronical Engineering, Beijing Institute of Technology
State Key Laboratory of Remote Sensing Science, Beijing Normal University
0