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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...
Autores principales: | Taheri-Garavand, Amin, Nasiri, Amin, Fanourakis, Dimitrios, Fatahi, Soodabeh, Omid, Mahmoud, Nikoloudakis, Nikolaos |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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Materias: | |
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 |
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