Quantitative detection and sorting of broken kernels and chalky grains in milled rice using computer vision algorithms-Reference-Cited by-同舟云学术

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Quantitative detection and sorting of broken kernels and chalky grains in milled rice using computer vision algorithms

Published:2024-12 Issue: Volume:383 Page:112225
ISSN:0260-8774
Container-title:Journal of Food Engineering
language:en
Short-container-title:Journal of Food Engineering

Author:

Fan Fanghui,Chen Haoran,Gao Yi,Mou Tian^ORCID

Publisher

Elsevier BV

Reference28 articles.

1. Chemistry, structure, functionality and applications of rice starch;Amagliani;J. Cereal. Sci.,2016

2. Deep CNN-based damage classification of milled rice grains using a high-magnification image dataset;Bhupendra;Comput. Electron. Agric.,2022

3. Evaluating the spatial risk of bacterial foodborne diseases using vulnerability assessment and geographically weighted logistic regression;Bian;Rem. Sens.,2022

4. Colored rice quality inspection system using machine vision;Chen;J. Cereal. Sci.,2019

5. Physicochemical properties and Strength analysis of vitreous encapsulated solids for the safe delivery of β-Carotene;Cui;Food Res. Int.,2022

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