@misc{indiciae8358c3b8c67a,
  title = {Estimating soybean yields from high-temporal-resolution multi-source data using deep learning},
  author = {Yin, Jia [China Agricultural Univ., Beijing (China); Ministry of Agriculture and Rural Affairs (MARA), Beijing (China). Key Laboratory of Remote Sensing for Agri-Hazards] and Zhang, Rundong [China Agricultural Univ., Beijing (China); Ministry of Agriculture and Rural Affairs (MARA), Beijing (China). Key Laboratory of Remote Sensing for Agri-Hazards] and Zeng, Yelu [China Agricultural Univ., Beijing (China); Ministry of Agriculture and Rural Affairs (MARA), Beijing (China). Key Laboratory of Remote Sensing for Agri-Hazards] (ORCID:0009000733470550) and Zhu, Peng [Univ. of Hong Kong, Pokfulam (Hong Kong)] and Yin, Leikun [Univ. of Minnesota, Saint Paul, MN (United States)] and Ma, Yuchi [Stanford Univ., CA (United States)] and Su, Wei [China Agricultural Univ., Beijing (China); Ministry of Agriculture and Rural Affairs (MARA), Beijing (China). Key Laboratory of Remote Sensing for Agri-Hazards] and Huang, Jianxi [Southwest Jiaotong Univ., Chengdu (China)] and Li, Xuecao [China Agricultural Univ., Beijing (China); Ministry of Agriculture and Rural Affairs (MARA), Beijing (China). Key Laboratory of Remote Sensing for Agri-Hazards] and Hao, Dalei [Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)]},
  year = {2025},
  doi = {10.1016/j.compag.2025.111283},
  url = {https://www.osti.gov/biblio/3013599},
  note = {Source identifier: 3013599}
}