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A deep learning method for predicting lead content in oilseed rape leaves using fluorescence hyperspectral imaging.

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第一作者： Xin,Zhou

第一单位： School of Electrical and Information Engineering of Jiangsu University, Zhenjiang 212013, China. Electronic address: 862218958@qq.com.

作者： Xin,Zhou ^[1] ; Chunjiang,Zhao ^[2] ; Jun,Sun ^[3] ; Yan,Cao ^[4] ; Kunshan,Yao ^[4] ; Min,Xu ^[4]

作者单位： School of Electrical and Information Engineering of Jiangsu University, Zhenjiang 212013, China. Electronic address: 862218958@qq.com. ^[1] School of Electrical and Information Engineering of Jiangsu University, Zhenjiang 212013, China; National Engineering Research Center for Information Technology in Agriculture, Beijing 100097, China; National Engineering Laboratory for Agri-product Quality Traceability, Beijing 100097, China. ^[2] School of Electrical and Information Engineering of Jiangsu University, Zhenjiang 212013, China. Electronic address: sun2000jun@sina.com. ^[3] School of Electrical and Information Engineering of Jiangsu University, Zhenjiang 212013, China. ^[4]

关键词 Fluorescence hyperspectral imaging Heavy metal lead Nondestructive testing Oilseed rape Stacked denoising autoencoder Wavelet transform

医学主题词谱学, 近红外线(Spectroscopy, Near-Infrared);最小二乘法分析(Least-Squares Analysis);欧洲油菜(Brassica napus);植物叶(Plant Leaves);算法(Algorithms)

DOI 10.1016/j.foodchem.2022.135251

PMID 36586261

发布时间 2023-02-01

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准确一般字义偏差语意偏离译文作用小提交