Automatic recognition of flow cytometric phytoplankton functional groups using convolutional neural networks - ARTICLE À COMITÉ DE LECTURE EN CYTOMÉTRIE EN FLUX APPLIQUÉE À L'OCÉANOGRAPHIE ET LA MICROBIOLOGIE Access content directly
Journal Articles Limnology and Oceanography: Methods Year : 2022

Automatic recognition of flow cytometric phytoplankton functional groups using convolutional neural networks

Robin Fuchs
Institut de Mathématiques de Marseille
Melilotus Thyssen
Institut méditerranéen d'océanologie
CV
Véronique Creach
Centre for Environment, Fisheries and Aquaculture Science [Lowestoft]
Mathilde Dugenne
University of Hawaii
Lloyd Izard
Processus et interactions de fine échelle océanique
Marie Latimier
  • Function : Author
Unité Dynamiques des Écosystèmes Côtiers
Arnaud Louchart
Stazione Zoologica Anton Dohrn
Pierre Marrec
Graduate School of Oceanography [Narragansett]
Machteld Rijkeboer
RWS RIJKSWATERSTAAT CENTRE FOR WATER MANAGEMENT LELYSTAD NLD
Gérald Grégori
Institut méditerranéen d'océanologie
CV
Denys Pommeret
Laboratoire de Sciences Actuarielle et Financière

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Ocean, Atmosphere
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https://amu.hal.science/hal-03688058

Submitted on : Wednesday, November 23, 2022-11:41:20 AM

Last modification on : Friday, April 26, 2024-2:36:21 PM

Long-term archiving on: Friday, February 24, 2023-6:47:07 PM

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hal-03688058 , version 1 (23-11-2022)

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Robin Fuchs, Melilotus Thyssen, Véronique Creach, Mathilde Dugenne, Lloyd Izard, et al.. Automatic recognition of flow cytometric phytoplankton functional groups using convolutional neural networks. Limnology and Oceanography: Methods, 2022, ⟨10.1002/lom3.10493⟩. ⟨hal-03688058⟩

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