Machine learning for high-throughput field phenotyping and image processing provides insight into the association of above and below-ground traits in cassava (Manihot esculenta Crantz)

scientific article published on 14 June 2020

Machine learning for high-throughput field phenotyping and image processing provides insight into the association of above and below-ground traits in cassava (Manihot esculenta Crantz) is …
instance of (P31):
scholarly articleQ13442814

External links are
P356DOI10.1186/S13007-020-00625-1
P932PMC publication ID7296968
P698PubMed publication ID32549903

P50authorMichael Gomez SelvarajQ91287511
P2093author name stringHenry Ruiz
Animesh Acharjee
Diego Guzman
Manuel Valderrama
Milton Valencia
P4510describes a project that usesscikit-imageQ22442795
scikit-learnQ1026367
P921main subjectmachine learningQ2539
Manihot EsculentaQ83124
P304page(s)87
P577publication date2020-06-14
P1433published inPlant MethodsQ15762916
P1476titleMachine learning for high-throughput field phenotyping and image processing provides insight into the association of above and below-ground traits in cassava (Manihot esculenta Crantz)
P478volume16

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