A Self Training Mechanism With Scanty and Incompletely Annotated Samples for Learning‐Based Cloud Detection in Whole Sky Images
Abstract Cloud detection is one of important tasks in automatic ground‐based cloud observation systems with ground‐based cloud images. Most supervised methods need substantial annotated samples for model training, while the pixel‐level annotation costs a lot. In this letter, a self‐training mechanis...
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
American Geophysical Union (AGU)
2022-06-01
|
| Series: | Earth and Space Science |
| Subjects: | |
| Online Access: | https://doi.org/10.1029/2022EA002220 |