Articles | Volume 13, issue 5
https://doi.org/10.5194/amt-13-2219-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-13-2219-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
08 May 2020
Research article |
| 08 May 2020
| 08 May 2020
A convolutional neural network for classifying cloud particles recorded by imaging probes
Georgios Touloupas
Institute for Machine Learning, ETH Zurich, Zurich, Switzerland
Institute for Atmospheric and Climate Science, ETH Zurich, Zurich, Switzerland
Jan Henneberger
CORRESPONDING AUTHOR
Institute for Atmospheric and Climate Science, ETH Zurich, Zurich, Switzerland
Alexander Beck
Institute for Atmospheric and Climate Science, ETH Zurich, Zurich, Switzerland
Aurélien Lucchi
Institute for Machine Learning, ETH Zurich, Zurich, Switzerland
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- Understanding the History of Two Complex Ice Crystal Habits Deduced From a Holographic Imager J. Pasquier et al. https://doi.org/10.1029/2022GL100247
- Discrimination and Measurement of Droplet and Ice Crystal by Combining Digital Inline Holography With Interferometric Particle Imaging With Single Color Camera Y. Wu et al. https://doi.org/10.1109/TIM.2022.3147333
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- Microphysical detection of nano-ice nuclei to ice crystals: a platform for ice nucleation research D. Pal et al. https://doi.org/10.1038/s41612-025-01062-4
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- Putting the spotlight on small cloud droplets with SmHOLIMO – a new holographic imager for in situ measurements of clouds C. Fuchs et al. https://doi.org/10.5194/amt-18-2969-2025
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Saved (final revised paper)
Latest update: 13 Sep 2026
Short summary
Images of cloud particles give important information for improving our understanding of microphysical cloud processes. For phase-resolved measurements, a large number of water droplets and ice crystals need to be classified by an automated approach. In this study, a convolutional neural network was designed, which exceeds the classification ability of traditional methods and therefore shortens the analysis procedure of cloud particle images.
Images of cloud particles give important information for improving our understanding of...
