Corpus ID: 207853174

Cumulo: A Dataset for Learning Cloud Classes

@article{Zantedeschi2019CumuloAD,
  title={Cumulo: A Dataset for Learning Cloud Classes},
  author={Valentina Zantedeschi and Fabrizio Falasca and A. Douglas and Richard Strange and Matt J. Kusner and D. Watson-Parris},
  journal={ArXiv},
  year={2019},
  volume={abs/1911.04227}
}
One of the greatest sources of uncertainty in future climate projections comes from limitations in modelling clouds and in understanding how different cloud types interact with the climate system. A key first step in reducing this uncertainty is to accurately classify cloud types at high spatial and temporal resolution. In this paper, we introduce Cumulo, a benchmark dataset for training and evaluating global cloud classification models. It consists of one year of 1km resolution MODIS… Expand
5 Citations
Sen1Floods11: a georeferenced dataset to train and test deep learning flood algorithms for Sentinel-1
  • 5
  • PDF
Data-driven Cloud Clustering via a Rotationally Invariant Autoencoder
  • PDF
Interval Deep Learning for Uncertainty Quantification in Safety Applications
  • PDF

References

SHOWING 1-10 OF 23 REFERENCES
Combining crowd-sourcing and deep learning to understand meso-scale organization of shallow convection
  • 6
  • Highly Influential
  • PDF
Focal Loss for Dense Object Detection
  • 4,456
Focal Loss for Dense Object Detection
  • 2,546
  • PDF
Weakly- and Semi-Supervised Panoptic Segmentation
  • 75
  • PDF
...
1
2
3
...