GS-DeepLabV3+: A mountain tea disease segmentation network based on improved shuffle attention and gated multidimensional feature extraction-Reference-Cited by-同舟云学术

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GS-DeepLabV3+: A mountain tea disease segmentation network based on improved shuffle attention and gated multidimensional feature extraction

Published:2024-09 Issue: Volume:183 Page:106762
ISSN:0261-2194
Container-title:Crop Protection
language:en
Short-container-title:Crop Protection

Author:

Zhou Hao,Peng Yuting,Zhang Ruopeng^ORCID,He Yushan,Li Lin,Xiao Wei

Publisher

Elsevier BV

Reference45 articles.

1. A fuzzy clustering segmentation method based on neighborhood grayscale information for defining cucumber leaf spot disease images;Bai;Comput. Electron. Agric.,2017

2. Classification of camellia oleifera diseases in complex environments by attention and multi-rrimensional feature fusion neural network;Chen;Plants,2023

3. Research progress and management strategies of fungal diseases in Camellia oleifera;Chen;Front. Microbiol.,2023

4. LightFGCNet: a lightweight and focusing on global context information semantic segmentation network for remote sensing imagery;Chen;Rem. Sens.,2022

5. Localizing plucking points of tea leaves using deep convolutional neural networks;Chen;Comput. Electron. Agric.,2020

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