A novel deep learning framework for High-Throughput peanut seedling identification across diverse germplasm and complex field environments
- DOI
- 10.1016/j.jag.2025.105061
- Published
- 2026-02
- Container
- International Journal of Applied Earth Observation and Geoinformation
- Publisher
- Elsevier BV
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1016/j.jag.2025.105061,
title = {A novel deep learning framework for High-Throughput peanut seedling identification across diverse germplasm and complex field environments},
author = {Jiangtao Zhao and Zhenhai Li and Bo Bai and Xue Kong and Jishun Yang and Guowei Li and Tadese Anberbir and Xiaobin Xu},
year = {2026},
journal = {International Journal of Applied Earth Observation and Geoinformation},
doi = {10.1016/j.jag.2025.105061},
url = {https://doi.org/10.1016/j.jag.2025.105061}
}RIS
TY - JOUR TI - A novel deep learning framework for High-Throughput peanut seedling identification across diverse germplasm and complex field environments AU - Jiangtao Zhao AU - Zhenhai Li AU - Bo Bai AU - Xue Kong AU - Jishun Yang AU - Guowei Li AU - Tadese Anberbir AU - Xiaobin Xu PY - 2026 JO - International Journal of Applied Earth Observation and Geoinformation DO - 10.1016/j.jag.2025.105061 UR - https://doi.org/10.1016/j.jag.2025.105061 ER -
APA
Zhao, J., Li, Z., Bai, B., Kong, X., Yang, J., Li, G., Anberbir, T., & Xu, X. (2026). A novel deep learning framework for High-Throughput peanut seedling identification across diverse germplasm and complex field environments. International Journal of Applied Earth Observation and Geoinformation. https://doi.org/10.1016/j.jag.2025.105061
Source records
- crossref · retrieved 2026-09-27T07:03:40.564Z