Identification of rice leaf disease based on DepMulti-Net

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成果类型：

期刊论文

作者：

Hu, Kui;Zheng, Xinying;Su, Xinyao;Wu, Lei;Liu, Yongmin;...

通讯作者：

Liu, YM

作者机构：

[Liu, Yongmin; Liu, YM; Hu, Kui] Cent South Univ Forestry & Technol, Sch Elect Informat & Phys, Changsha, Hunan, Peoples R China.

[Liu, Yongmin; Zheng, Xinying; Liu, YM; Hu, Kui] Cent South Univ Forestry & Technol, Res Ctr Smart Forestry Cloud, Changsha, Hunan, Peoples R China.

[Zheng, Xinying] Hunan Normal Univ, Sch Business, Changsha, Hunan, Peoples R China.

[Su, Xinyao] Cent South Univ Forestry & Technol, Sch Bangor, Changsha, Hunan, Peoples R China.

[Wu, Lei] Cent South Univ Forestry & Technol, Sch Forestry, Changsha, Hunan, Peoples R China.

通讯机构：

[Liu, YM ] C

Cent South Univ Forestry & Technol, Sch Elect Informat & Phys, Changsha, Hunan, Peoples R China.

Cent South Univ Forestry & Technol, Res Ctr Smart Forestry Cloud, Changsha, Hunan, Peoples R China.

语种：

英文

关键词：

DepMulti-Net;convolutional Neural Network;depthseparable convolution;feature reuse;multi-scale feature fusion;rice leaf diseases

期刊：

FRONTIERS IN PLANT SCIENCE

ISSN：

1664-462X

年：

2025

卷：

页码：

1522487

DOI：

10.3389/fpls.2025.1522487

基金类别：

The author(s) declare that financial support was received for the research and/or publication of this article. This research is funded by National Natural Science Foundation of China (Grant No. 31870532); Changsha Science and Technology Plan Project (Grant No. kq2402265); Hunan Normal University (Grant No. 202048JG14).

机构署名：

本校为第一且通讯机构

院系归属：

林学院

摘要：

This research presents DepMulti-Net, a novel rice disease and pest identification model, designed to overcome the challenges of complex background interference, difficult disease feature extraction, and large model parameter volume in rice leaf disease identification. Initially, a comprehensive rice disease dataset comprising 20,000 images was meticulously constructed, covering four common types of rice diseases: bacterial leaf blight, rice blast, brown spot, and tungro disease. To enhance data diversity, various data augmentation techniques were applied. Subsequently, a novel VGG-block module...

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Identification of rice leaf disease based on DepMulti-Net

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