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Fusion of the deep networks for rapid detection of branch-infected aeroponically cultivated mulberries using multimodal traits

Osama Elsherbiny Jianmin Gao Yinan Guo Mazhar H.Tunio Abdallah H.Mosha

International Journal of Agricultural and Biological Engineering2025，Vol.18Issue(2)：P.75-88,14.

International Journal of Agricultural and Biological Engineering2025，Vol.18Issue(2)：P.75-88,14.DOI:10.25165/j.ijabe.20251802.8666

Fusion of the deep networks for rapid detection of branch-infected aeroponically cultivated mulberries using multimodal traits

Osama Elsherbiny ¹Jianmin Gao ²Yinan Guo ²Mazhar H.Tunio ²Abdallah H.Mosha²

作者信息

1. School of Agricultural Engineering,Jiangsu University,Zhenjiang 212013,China Agricultural Engineering Department,Faculty of Agriculture,Mansoura University,Mansoura 35516,Egypt
2. School of Agricultural Engineering,Jiangsu University,Zhenjiang 212013,China
折叠

摘要

关键词

mulberry twigs health/digital imagery/VIs-GLCM/top features selection/CNN-GRU/aeroponic system

分类

信息技术与安全科学

引用本文复制引用

Osama Elsherbiny,Jianmin Gao,Yinan Guo,Mazhar H.Tunio,Abdallah H.Mosha..Fusion of the deep networks for rapid detection of branch-infected aeroponically cultivated mulberries using multimodal traits[J].International Journal of Agricultural and Biological Engineering,2025,18(2):P.75-88,14.

基金项目

support provided by the National Natural Science Foundation of China Program(Grant No.51975255) （Grant No.51975255）

the Project Funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions(Grant No.PAPD-2018-87) （Grant No.PAPD-2018-87）

the Jiangsu Funding Program for Excellent Postdoctoral Talent(Grant No.2023ZB888). （Grant No.2023ZB888）

International Journal of Agricultural and Biological Engineering

ISSN：1934-6344

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