A scalable pipeline to create synthetic datasets from functional–structural plant models for deep le...
A scalable pipeline to create synthetic datasets from functional–structural plant models for deep learning
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Publisher
UK: Oxford University Press
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Language
English
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Publisher
UK: Oxford University Press
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Abstract
In plant science, it is an established method to obtain structural parameters of crops using image analysis. In recent years, deep learning techniques have improved the underlying processes significantly. However, since data acquisition is time and resource consuming, reliable training data are currently limited. To overcome this bottle...
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Full title
A scalable pipeline to create synthetic datasets from functional–structural plant models for deep learning
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TN_cdi_proquest_journals_3168783040
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_3168783040
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ISSN
2517-5025
E-ISSN
2517-5025
DOI
10.1093/insilicoplants/diad022
