Next-generation high-throughput phenotyping with trait prediction through adaptable multi-task computational intelligence
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De Diego Sanchez, Nuria; Saiz-Fernández, Iñigo;
Next-generation high-throughput phenotyping with trait prediction through adaptable multi-task computational intelligence
Dataset containing pictures of potato plants grown in vitro used for validation of our AMULET pipeline, which is publiced in the article titled "Next-generation high-throughput phenotyping with trait prediction through adaptable multi-task computational intelligence". The codes and rest of materials for AMULET pipeline can be found in the following link, GitHub: https://github.com/JZdrazilX/DigGreen/tree/main
- Palacký University, Olomouc Czech Republic
Machine Learning, general purposes, Plant Phenotyping, in vitro cultures, latent phenon, phenotyping markers
Machine Learning, general purposes, Plant Phenotyping, in vitro cultures, latent phenon, phenotyping markers
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selected citations
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These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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