ArticleApplications in plant sciences
An automated pipeline for supervised classification of petal color from citizen science photographs.
Article in Applications in plant sciences. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Delayed flowering phenology of red-flowering plants in response to hummingbird migration.Current biology : CB · 2025Article
- Review
- Extracting secondary data from citizen science images reveals host flower preferences of the Mexican grass-carrying waspEcology and evolution · 2024Article
- An automated pipeline for supervised classification of petal color from citizen science photographs.Applications in plant sciencesArticle
- A pipeline for the rapid collection of color data from photographs.Applications in plant sciencesArticle
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Premise: Petal color is an ecologically important trait, and uncovering color variation over a geographic range, particularly in species with large distributions and/or short bloom times, requires extensive fieldwork. We have developed an alternative method that segments images from citizen science repositories using Python and Methods: Our method uses Results: We demonstrate the application of this method using two species: one with a continuous range of variation of pink-purple petals in Discussion: This method provides a flexible, robust, and easily adjustable approach for the classification of color images from citizen science repositories. By using color to classify images, this pipeline sidesteps many of the issues encountered using more traditional computer vision applications. This approach provides a tool for making use of large citizen scientist data sets.
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