Exploring the effect of training set size and number of categories on ice crystal classification through a contrastive semi-supervised learning algorithm
<p>The shapes of ice crystals play an important role in global precipitation formation and the radiation budget. Classifying ice crystal shapes can improve our understanding of in-cloud conditions and these processes. Existing classification methods rely on features such as the aspect ratio of...
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2025-06-01
|
| Series: | Atmospheric Measurement Techniques |
| Online Access: | https://amt.copernicus.org/articles/18/2781/2025/amt-18-2781-2025.pdf |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|