Automated In Situ Seed Variety Identification via Deep Learning: A Case Study in Chickpea

On-time seed variety recognition is critical to limit qualitative and quantitative yield loss and asynchronous crop production. The conventional method is a subjective and error-prone process, since it relies on human experts and usually requires accredited seed material. This paper presents a convo...

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Detalles Bibliográficos
Autores principales: Taheri-Garavand, Amin, Nasiri, Amin, Fanourakis, Dimitrios, Fatahi, Soodabeh, Omid, Mahmoud, Nikoloudakis, Nikolaos
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8309301/
https://www.ncbi.nlm.nih.gov/pubmed/34371609
http://dx.doi.org/10.3390/plants10071406

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8309301/
https://www.ncbi.nlm.nih.gov/pubmed/34371609
http://dx.doi.org/10.3390/plants10071406

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