Automated taxonomic classification of phytoplankton sampled with imaging‐in‐flow cytometry

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Advancing Marine Biological Observations and Data Requirements of the Complementary Essential Ocean Variables (EOVs) and Essential Biodiversity Variables (EBVs) Frameworks (2018, methodology): “The Video Plankton Recorder (VPR; Davis et al., 1992), Optical Plankton Recorder, and Imaging FlowCytoBot (Olson and Sosik, 2007; Sosik and Olson, 2007) are examples of submersible microscopes used to collect video or images of small organisms, cells, and particles.”
FlowCAM: Sizing cells and understanding the impact of size distributions on biovolume of planktonic community structure (2011, background): “These instruments are available as submersible units (Sosik & Olson 2007, Campbell et al. 2008, Thyssen et al. 2008) and as onboard instrumentation on auton o - mous underwater vehicles (Cunningham et al. 2003).”
Plankton classification on imbalanced large scale database via convolutional neural networks with transfer learning (2016, background): “Since these imaging systems often generates a large amount of image data, the presence of automated techniques for pattern recognition and classification of plankton images [2, 3, 4] has also been requested.”