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Integrating UAV remote sensing and semi-supervised learning for early-stage maize seedling monitoring and geolocation

Rui Yang Mengyuan Chen Xiangyu Lu Yong He Yanmei Li Mingliang Xu Mu Li Wei Huang Fei Liu

Plant Phenomics2025，Vol.7Issue(1)：P.102-113,12.

Plant Phenomics2025，Vol.7Issue(1)：P.102-113,12.DOI:10.1016/j.plaphe.2025.100011

Integrating UAV remote sensing and semi-supervised learning for early-stage maize seedling monitoring and geolocation

Rui Yang ¹Mengyuan Chen ¹Xiangyu Lu ¹Yong He ¹Yanmei Li ²Mingliang Xu ²Mu Li ³Wei Huang ³Fei Liu¹

作者信息

1. College of Biosystems Engineering and Food Science,Zhejiang University,Hangzhou,310058,China
2. National Maize Improvement Centre of China,China Agricultural University,Beijing,100193,China
3. Maize Research Institute,Jilin Academy of Agricultural Sciences,Gongzhuling City,136100,China
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摘要

关键词

Maize seedling/Emergence rate/UAV image/Semi-supervised object detection/Direct geolocation

分类

农业科技

引用本文复制引用

Rui Yang,Mengyuan Chen,Xiangyu Lu,Yong He,Yanmei Li,Mingliang Xu,Mu Li,Wei Huang,Fei Liu..Integrating UAV remote sensing and semi-supervised learning for early-stage maize seedling monitoring and geolocation[J].Plant Phenomics,2025,7(1):P.102-113,12.

基金项目

supported by National Key R&D Program of China(2023YFD2000203) （2023YFD2000203）

Science and Technology Department of Zhejiang Province(2022C02034). （2022C02034）

Plant Phenomics

ISSN：2097-0374

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