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Computer vision and machine learning for robust phenotyping in genome-wide studies
Traditional evaluation of crop biotic and abiotic stresses are time-consuming and labor-intensive limiting the ability to dissect the genetic basis of quantitative traits. A machine learning (ML)-enabled image-phenotyping pipeline for the genetic studies of abiotic stress iron deficiency chlorosis (...
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| Publicado no: | Sci Rep |
|---|---|
| Main Authors: | , , , , , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
Nature Publishing Group
2017
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC5358742/ https://ncbi.nlm.nih.gov/pubmed/28272456 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1038/srep44048 |
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