DOI: 10.1007/s11356-021-12471-2

Dataset	Relation
Cell abundances for taxonomic groups from manually corrected live Imaging FlowCytobot (IFCB) analysis of water samples collected from surface and chlorophyll maximum depths during R/V Pt. Sur cruise PS 18-09 in the western Gulf of Mexico, Sept-Oct 2017	Results
Biomass of taxonomic groups from manually corrected live Imaging FlowCytobot (IFCB) analysis of water samples collected from surface and chlorophyll maximum depths during R/V Pt. Sur cruise PS 18-09 in the western Gulf of Mexico, Sept-Oct 2017	Results
Cell abundances of taxonomic groups determined using a custom convolutional neural network from live Imaging FlowCytobot (IFCB) at seven stations sampled during R/V Pt. Sur cruise PS 18-09 in the western Gulf of Mexico, Sept-Oct 2017.	Results

Citation Style:

APA

Citation Text:

Henrichs, D. W., Anglès, S., Gaonkar, C. C., & Campbell, L. (2021). Application of a convolutional neural network to improve automated early warning of harmful algal blooms. Environmental science and pollution research international, 28(22), 28544–28555. https://doi.org/10.1007/s11356-021-12471-2

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DOI

Identifier Value:

10.1007/s11356-021-12471-2

Resource Type:

Publication

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DOI: 10.1007/s11356-021-12471-2