Fusion of hyperspectral imaging (HSI) and RGB for identification of soybean kernel damages using ShuffleNet with convolutional optimization and cross stage partial architecture

Fusion of hyperspectral imaging (HSI) and RGB for identification of soybean kernel damages using ShuffleNet with convolutional optimization and cross stage partial architecture

Identification of soybean kernel damages is significant to prevent further disoperation. Hyperspectral imaging (HSI) has shown great potential in cereal kernel identification, but its low spatial resolution leads to external feature infidelity and limits the analysis accuracy. In this study, the fus...

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Bibliographic Details
Main Authors: Ling Zheng, Mingyue Zhao, Jinchen Zhu, Linsheng Huang, Jinling Zhao, Dong Liang, Dongyan Zhang
Format: Article
Language:English
Published: Frontiers Media S.A. 2023-01-01
Series:Frontiers in Plant Science
Subjects:
soybean damages
hyperspectral imaging
super resolution
image fusion
lightweight deep learning
Online Access:https://www.frontiersin.org/articles/10.3389/fpls.2022.1098864/full

Internet

https://www.frontiersin.org/articles/10.3389/fpls.2022.1098864/full

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