A deep learning model based on RGB and hyperspectral images for efficiently detecting tea green leafhopper damage symptoms

A deep learning model based on RGB and hyperspectral images for efficiently detecting tea green leafhopper damage symptoms

The tea green leafhopper, also known as ''Empoasca onukii Matsuda,'' is a common pest of tea plants that can cause significant economic losses when its damage becomes severe. However, traditional methods of recognizing and classifying the damage symptoms of this pest rely on huma...

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Bibliographic Details
Main Authors: Yang Xu, Yilin Mao, He Li, Jiazhi Shen, Xiuxiu Xu, Shuangshuang Wang, Shah Zaman, Zhaotang Ding, Yu Wang
Format: Article
Language:English
Published: Elsevier 2025-03-01
Series:Smart Agricultural Technology
Subjects:
Tea green leafhopper
RGB
Hyperspectral
Machine learning
Deep learning
Classification
Online Access:http://www.sciencedirect.com/science/article/pii/S2772375525000516
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