Improving classification of pollen grain images of the POLEN23E dataset through three different applications of deep learning convolutional neural networks

In palynology, the visual classification of pollen grains from different species is a hard task which is usually tackled by human operators using microscopes. Its complete automatization would save a high quantity of resources and provide valuable improvements especially for allergy-related informat...

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Detalles Bibliográficos
Autores principales: Sevillano, Víctor, Aznarte, José L.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2018
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6138340/
https://www.ncbi.nlm.nih.gov/pubmed/30216353
http://dx.doi.org/10.1371/journal.pone.0201807

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6138340/
https://www.ncbi.nlm.nih.gov/pubmed/30216353
http://dx.doi.org/10.1371/journal.pone.0201807

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