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Open Access

Peer-reviewed

Research Article

Precise automatic classification of 46 different pollen types with convolutional neural networks

Víctor Sevillano,

Roles Data curation, Investigation, Software, Visualization, Writing – original draft

Affiliation Artificial Intelligence Department, Universidad Nacional de Educación a Distancia—UNED, Madrid, Spain
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Katherine Holt,

Roles Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Resources, Validation, Writing – original draft, Writing – review & editing

Affiliation Institute of Natural Resources, Massey University, Palmerston North, New Zealand
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José L. Aznarte

Roles Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Supervision, Validation, Visualization, Writing – original draft, Writing – review & editing

* E-mail: jlaznarte@dia.uned.es

Affiliation Artificial Intelligence Department, Universidad Nacional de Educación a Distancia—UNED, Madrid, Spain

http://orcid.org/0000-0002-1636-244X

⨯

Precise automatic classification of 46 different pollen types with convolutional neural networks

Víctor Sevillano,
Katherine Holt,
José L. Aznarte

x

Published: June 23, 2020
https://doi.org/10.1371/journal.pone.0229751
See the preprint

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Pollen
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Neural networks
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Deep learning
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Imaging techniques
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Honey
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Machine learning
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Preprocessing
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Recurrent neural networks
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