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Computer vision and machine learning enabled soybean root phenotyping pipeline
BACKGROUND: Root system architecture (RSA) traits are of interest for breeding selection; however, measurement of these traits is difficult, resource intensive, and results in large variability. The advent of computer vision and machine learning (ML) enabled trait extraction and measurement has rene...
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| 出版年: | Plant Methods |
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| 主要な著者: | , , , , , , , |
| フォーマット: | Artigo |
| 言語: | Inglês |
| 出版事項: |
BioMed Central
2020
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| 主題: | |
| オンライン・アクセス: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6977263/ https://ncbi.nlm.nih.gov/pubmed/31993072 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1186/s13007-019-0550-5 |
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