Leveraging Unsupervised Methods to Train Image Classification Networks with Fewer Labelled Inputs: Application to Species Classification of Phytoplankton Imagery from an Imaging Flow Cytometer

Culhane, Emmett

Leveraging Unsupervised Methods to Train Image Classification Networks with Fewer Labelled Inputs: Application to Species Classification of Phytoplankton Imagery from an Imaging Flow Cytometer

Emmett Culhane, Yale University, United States, Nils Haentjens, University of Maine, Orono, ME, United States, Alison P Chase, University of Maine, School of Marine Science, Orono, ME, United States, Peter Gaube, Applied Physics Laboratory at the University of Washington, Air-Sea Interaction and Remote Sensing, Seattle, WA, United States and Jason Morrill, University of Maine, Orono, United States