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A hybrid CNN-LSTM model for diagnosing rice nutrient levels at the rice panicle initiation stage

Fubing Liao Xiangqian Feng Ziqiu Li Danying Wang Chunmei Xu Guang Chu Hengyu Ma Qing Yao Song Chen

Journal of Integrative Agriculture2024，Vol.23Issue(2)：P.711-723,13.

Journal of Integrative Agriculture2024，Vol.23Issue(2)：P.711-723,13.DOI:10.1016/j.jia.2023.05.032

A hybrid CNN-LSTM model for diagnosing rice nutrient levels at the rice panicle initiation stage

Fubing Liao ¹Xiangqian Feng ²Ziqiu Li ¹Danying Wang ³Chunmei Xu ³Guang Chu ³Hengyu Ma ³Qing Yao ¹Song Chen³

作者信息

1. School of Computer Science and Technology,Zhejiang Sci-Tech University,Hangzhou 310018,China
2. China National Rice Research Institute,Chinese Academy of Agricultural Sciences,Hangzhou 310006,China School of Agriculture,Yangtze University,Jingzhou 434025,China
3. China National Rice Research Institute,Chinese Academy of Agricultural Sciences,Hangzhou 310006,China
折叠

摘要

关键词

dynamic model of deep learning/UAV/rice panicle initiation/nutrient level diagnosis/image classification

分类

农业科学

引用本文复制引用

Fubing Liao,Xiangqian Feng,Ziqiu Li,Danying Wang,Chunmei Xu,Guang Chu,Hengyu Ma,Qing Yao,Song Chen..A hybrid CNN-LSTM model for diagnosing rice nutrient levels at the rice panicle initiation stage[J].Journal of Integrative Agriculture,2024,23(2):P.711-723,13.

基金项目

supported by the National Key Research and Development Program of China(2022YFD2300700) （2022YFD2300700）

the Open Project Program of State Key Laboratory of Rice Biology,China National Rice Research Institute(20210403) （20210403）

the Zhejiang“Ten Thousand Talents”Plan Science and Technology Innovation Leading Talent Project,China(2020R52035)。（2020R52035）

Journal of Integrative Agriculture

OACSTPCD

ISSN：2095-3119

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