paper
2020
Explainability, uncertainty & physics
Observations & remote sensing Review, survey or tutorial
CNN / U-NetOtherColorado State University (incl. CIRA) Journal
2020-08-31
036
Aug 2020
Imme Ebert‐Uphoff, Kyle Hilburn
Bulletin of the American Meteorological Society
Colorado State University (incl. CIRA)
Tutorial-style guidance on evaluating, tuning and interpreting neural networks for meteorological satellite images, covering receptive fields, relevance propagation and image-to-image translation.
Explainability, uncertainty & physics
Evaluation, Tuning, and Interpretation of Neural Networks for Working with Images in Meteorological Applications
In one sentence. Tutorial-style guidance on evaluating, tuning and interpreting neural networks for meteorological satellite images, covering receptive fields, relevance propagation and image-to-image translation.
Labels
- Topic
- Explainability, uncertainty & physics, Observations & remote sensing
- Type
- Review, survey or tutorial
- Method
- CNN / U-Net, Other
- Data
- Satellite
- Status
- Research
- Identifiers
- DOI:10.1175/bams-d-20-0097.1 OpenAlex:W3082330840
- Added
- 2026-10-22
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