Towards operational phytoplankton recognition with automated high-throughput imaging, near-real-time data processing, and convolutional neural networks

Plankton communities form the basis of aquatic ecosystems and elucidating their role in increasingly important environmental issues is a persistent research question. Recent technological advances in automated microscopic imaging, together with cloud platforms for high-performance computing, have cr...

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Veröffentlicht in:	Frontiers in Marine Science Jg. 9
Hauptverfasser:	Kraft, Kaisa, Velhonoja, Otso, Eerola, Tuomas, Suikkanen, Sanna, Tamminen, Timo, Haraguchi, Lumi, Ylöstalo, Pasi, Kielosto, Sami, Johansson, Milla, Lensu, Lasse, Kälviäinen, Heikki, Haario, Heikki, Seppälä, Jukka
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Frontiers Media S.A 02.09.2022
Schlagworte:	automated data processing convolutional neural network IFCB imaging flow cytometry (IFC) near-real-time classification phytoplankton imaging
ISSN:	2296-7745, 2296-7745
Online-Zugang:	Volltext
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