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Towards operational phytoplankton recognition with automate..:

Kaisa Kraft ; Otso Velhonoja ; Tuomas Eerola...
https://www.frontiersin.org/articles/10.3389/fmars.2022.867695/full. , 2022

Link: https://doi.org/10.3389/fmars.2022.867695

RT Journal
T1 <Title>Towards operational phytoplankton recognition with automated high-throughput imaging, near-real-time data processing, and convolutional neural networks</Title>

UL https://suche.suub.uni-bremen.de/peid=base-ftdoajarticles:oai:doaj.org_article:3883e8a950e64409b554283c6f6cda49&Exemplar=1&LAN=DE
				
A1 Kaisa Kraft
A1 Otso Velhonoja
A1 Tuomas Eerola
A1 Sanna Suikkanen
A1 Timo Tamminen
A1 Lumi Haraguchi
A1 Pasi Ylöstalo
A1 Sami Kielosto
A1 Milla Johansson
A1 Lasse Lensu
A1 Heikki Kälviäinen
A1 Heikki Haario
A1 Jukka Seppälä
PB Frontiers Media S.A.
YR 2022
K1 IFCB
K1 near-real-time classification
K1 phytoplankton imaging
K1 automated data processing
K1 imaging flow cytometry (IFC)
K1 convolutional neural network
K1 Science
K1 Q
K1 General. Including nature conservation
K1 geographical distribution
K1 QH1-199.5
JF https://www.frontiersin.org/articles/10.3389/fmars.2022.867695/full
LK http://dx.doi.org/https://doi.org/10.3389/fmars.2022.867695
DO https://doi.org/10.3389/fmars.2022.867695
SF ELIB - SuUB Bremen

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