Niccolò Maffezzoli, Eliza Cook, Willem G. M. van der Bilt, Eivind N. Støren, Daniela Festi, Florian Muthreich, Alistair W. R. Seddon, François Burgay, Giovanni Baccolo, Amalie R. F. Mygind, Troels Petersen, Andrea Spolaor, Sebastiano Vascon, Marcello Pelillo, Patrizia Ferretti, Rafael S. dos Reis, Jefferson C. Simões, Yuval Ronen, Barbara Delmonte, Marco Viccaro, Jørgen Peder Steffensen, Dorthe Dahl-Jensen, Kerim H. Nisancioglu, and Carlo Barbante
The Cryosphere, 17, 539–565, https://doi.org/10.5194/tc-17-539-2023,https://doi.org/10.5194/tc-17-539-2023, 2023
Multiple lines of research in ice core science are limited by manually intensive and time-consuming optical microscopy investigations for the detection of insoluble particles, from pollen grains to volcanic shards. To help overcome these limitations and support researchers, we present a novel methodology for the identification and autonomous classification of ice core insoluble particles based on flow image microscopy and neural networks.
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