Improving the taxonomy of fossil pollen using convolutional neural networks and superresolution microscopy

Taxonomic resolution is a major challenge in palynology, largely limiting the ecological and evolutionary interpretations possible with deep-time fossil pollen data. We present an approach for fossil pollen analysis that uses optical superresolution microscopy and machine learning to create a quanti...

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Dettagli Bibliografici
Pubblicato in:Proc Natl Acad Sci U S A
Autori principali: Romero, Ingrid C., Kong, Shu, Fowlkes, Charless C., Jaramillo, Carlos, Urban, Michael A., Oboh-Ikuenobe, Francisca, D’Apolito, Carlos, Punyasena, Surangi W.
Natura: Artigo
Lingua:Inglês
Pubblicazione: National Academy of Sciences 2020
Soggetti:
Biological Sciences
Accesso online:https://ncbi.nlm.nih.gov/pmc/articles/PMC7668113/
https://ncbi.nlm.nih.gov/pubmed/33097671
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1073/pnas.2007324117
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