Identification of Defective Maize Seeds Using Hyperspectral Imaging Combined with Deep Learning

Seed quality affects crop yield and the quality of agricultural products, and traditional identification methods are time-consuming, complex, and irreversibly destructive. This study aims to establish a fast, non-destructive, and effective approach for defect detection in maize seeds based on hypers...

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Detalles Bibliográficos
Autores principales: Xu, Peng, Sun, Wenbin, Xu, Kang, Zhang, Yunpeng, Tan, Qian, Qing, Yiren, Yang, Ranbing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9818215/
https://www.ncbi.nlm.nih.gov/pubmed/36613360
http://dx.doi.org/10.3390/foods12010144

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9818215/
https://www.ncbi.nlm.nih.gov/pubmed/36613360
http://dx.doi.org/10.3390/foods12010144

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