Detection of soluble solid content in apples based on hyperspectral technology combined with deep learning algorithm-Reference-Cited by-同舟云学术

Detection of soluble solid content in apples based on hyperspectral technology combined with deep learning algorithm

Published:2022-03-03 Issue:4 Volume:46 Page:
ISSN:0145-8892
Container-title:Journal of Food Processing and Preservation
language:en
Short-container-title:Food Processing Preservation

Author:

Tian Yan¹²^ORCID,Sun Jun¹^ORCID,Zhou Xin¹,Yao Kunshan¹^ORCID,Tang Ningqiu¹

Affiliation:

1. School of Electrical and Information Engineering Jiangsu University Zhenjiang China

2. School of Electronic Information Jiangsu University of Science and Technology Zhenjiang China

Publisher

Hindawi Limited

Subject

General Chemical Engineering,General Chemistry,Food Science

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/jfpp.16414

Reference35 articles.

1. Spectral‐spatial feature learning for hyperspectral imagery classification using deep stacked sparse autoencoder;Abdi G.;Journal of Applied Remote Sensing,2017

2. Auto‐encoder‐based shared mid‐level visual dictionary learning for scene classification using very high resolution remote sensing images

3. Non‐destructive detection for mold colonies in rice based on hyperspectra and GWO‐SVR;Cong S.;Journal of the Science of Food and Agriculture,2017

4. Nondestructive Determination of Apple Internal Qualities Using Near-Infrared Hyperspectral Reflectance Imaging

5. Prediction of soluble solids content of apple using the combination of spectra and textural features of hyperspectral reflectance imaging data

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