Study on Rice Grain Mildewed Region Recognition Based on Microscopic Computer Vision and YOLO-v5 Model

This study aims to develop a high-speed and nondestructive mildewed rice grain detection method. First, a set of microscopic images of rice grains contaminated by Aspergillus niger, Penicillium citrinum, and Aspergillus cinerea are acquired to serve as samples, and the mildewed regions are marked. T...

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Detalles Bibliográficos
Autores principales: Sun, Ke, Zhang, Yu-Jie, Tong, Si-Yuan, Tang, Meng-Di, Wang, Chang-Bao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9777938/
https://www.ncbi.nlm.nih.gov/pubmed/36553773
http://dx.doi.org/10.3390/foods11244031

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9777938/
https://www.ncbi.nlm.nih.gov/pubmed/36553773
http://dx.doi.org/10.3390/foods11244031

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