Articles | Volume 13, issue 6
Research article
05 Jun 2020
Research article |  | 05 Jun 2020

Unsupervised classification of snowflake images using a generative adversarial network and K-medoids classification

Jussi Leinonen and Alexis Berne


Interactive discussion

Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision
AR by Jussi Leinonen on behalf of the Authors (15 Apr 2020)  Author's response    Manuscript
ED: Publish as is (30 Apr 2020) by Daqing Yang
Short summary
The appearance of snowflakes provides a signature of the atmospheric processes that created them. To get this information from large numbers of snowflake images, automated analysis using computer image recognition is needed. In this work, we use a neural network that learns the structure of the snowflake images to divide a snowflake dataset into classes corresponding to different sizes and structures. Unlike with most comparable methods, only minimal input from a human expert is needed.