Articles | Volume 17, issue 2
Research article
07 Feb 2023
Research article |  | 07 Feb 2023

Detection of ice core particles via deep neural networks

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

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Cited articles

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Baccolo, G., Delmonte, B., Di Stefano, E., Cibin, G., Crotti, I., Frezzotti, M., Hampai, D., Iizuka, Y., Marcelli, A., and Maggi, V.: Deep ice as a geochemical reactor: insights from iron speciation and mineralogy of dust in the Talos Dome ice core (East Antarctica), The Cryosphere, 15, 4807–4822,, 2021. a
Bigler, M., Svensson, A., Kettner, E., Vallelonga, P., Nielsen, M. E., and Steffensen, J. P.: Optimization of high-resolution continuous flow analysis for transient climate signals in ice cores, Environ. Sci. Technol., 45, 4483–4489, 2011. a
Bohleber, P., Erhardt, T., Spaulding, N., Hoffmann, H., Fischer, H., and Mayewski, P.: Temperature and mineral dust variability recorded in two low-accumulation Alpine ice cores over the last millennium, Clim. Past, 14, 21–37,, 2018. a
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Short summary
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.