A convolutional neural network for classifying cloud particles recorded by imaging probes

Touloupas, Georgios; Lauber, Annika; Henneberger, Jan; Beck, Alexander; Lucchi, Aurélien

doi:https://doi.org/10.5194/amt-13-2219-2020

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.

https://doi.org/10.5194/amt-13-2219-2020

© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 13, issue 5

Research article

|

08 May 2020

Research article |

| 08 May 2020

A convolutional neural network for classifying cloud particles recorded by imaging probes

Georgios Touloupas, Annika Lauber, Jan Henneberger, Alexander Beck, and Aurélien Lucchi

Data sets

A Convolutional Neural Network for Classifying Cloud Particles Recorded by Imaging Probes A. Lauber and G. Touloupas https://doi.org/10.5281/zenodo.3715984

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.