PRIMAL

Official page Github repo

PRIMAL stands for a Pipeline of Root Image analysis using MAchine Learning. In short, the pipeline use Machine Learning techniques (Random Forest in particular), tu streamline the image analysis of large root dataset.

PRIMAL needs only a subset of the data to be analyse manual, instead of the full dataset. That subset is then used to train the algorithm behind PRIMAL the predict the parameters of interest, based on automatically acquired descriptors.


Associated papers

Combining semi-automated image analysis techniques with machine learning algorithms to accelerate large scale genetic studies | 2017 | Atkinson J*, Lobet G*, Noll M, Meyer P, Griffiths M, Wells D | View paper

Using a structural root system model for an in-depth assessment of root image analysis pipeline | 2017 | Lobet G*, Koevoets I T*, Noll M*, Meyer P, Tocquin P, Pagès L, Périlleux C | View paper


Associated presentations

Using structural models to validate and improve root image analysis pipelines | 2016 | View on figshare


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