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Yield Prediction Method for Regenerated Rice Based on Hyperspectral Image and Attention Mechanisms

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成果类型:
期刊论文
作者:
Hu, Tian;Liu, Zhihua;Hu, Rong;Zeng, Lu;Deng, Kaiwen;...
通讯作者:
Li, M;Deng, YJ
作者机构:
[Liu, Zhihua; Li, Ming; Li, M; Deng, Kaiwen; Hu, Tian; Dong, Huanglin] Hunan Acad Agr Sci, Hunan Agr Equipment Res Inst, Changsha 410125, Peoples R China.
[Hu, Rong] Hunan Agr Univ, Sch Food Sci & Technol, Changsha 410128, Peoples R China.
[Zeng, Lu] Hunan Agr Univ, Engn Res Ctr Hort Crop Germplasm Creat & New Varie, Changsha 410128, Peoples R China.
[Deng, Yang-Jun] Hunan Agr Univ, Coll Informat & Intelligence, Changsha 410128, Peoples R China.
通讯机构:
[Deng, YJ ; Li, M ] H
Hunan Acad Agr Sci, Hunan Agr Equipment Res Inst, Changsha 410125, Peoples R China.
Hunan Agr Univ, Coll Informat & Intelligence, Changsha 410128, Peoples R China.
语种:
英文
关键词:
Regenerated rice;Hyperspectral image;Convolutional neural network;Attention mechanism;Regenerated rice yield prediction
期刊:
Smart Agricultural Technology
ISSN:
2772-3755
年:
2025
卷:
10
页码:
100804
机构署名:
本校为通讯机构
院系归属:
食品科学技术学院
摘要:
Regenerated rice has the characteristics of dual harvest, labor-saving and cost-saving, which is of great significance for solving the global food problem. Hyperspectral image technology is one of the main methods to obtain vegetation canopy data on a large scale, which has the advantages of image and spectral information set in one, comprehensive information response, no need for pre-processing, non-polluting and non-destructive, etc. It mainly establishes a hyperspectral diagnostic model for crop yield through remote sensing data, assists in crop yield prediction, and finally uses Convolutio...

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