Published January 12, 2021
| Version v0.2-alpha
Software
Open
ML pipeline for Solar Dynamics Observatory (SDO) data
Authors/Creators
- 1. SETI Institute
- 2. The Catholic University of America/ NASA, Goddard Space Flight Center
- 3. Rosseland Center for Solar Physics, University of Oslo
- 4. Lockheed Martin Solar & Astrophysics Laboratory
- 5. Université Paris-Saclay, CNRS, Institut d'astrophysique spatiale
- 6. SETI Institute/Lockheed Martin Solar & Astrophysics Laboratory
- 7. OATML, Department of Computer Science, University of Oxford
- 8. Department of Engineering Science/Department of Computer Science, University of Oxford
Description
This software has been developed from the [FDL SDO Team](https://frontierdevelopmentlab.org/2019-sdo).
The package contains:
- a configurable pipeline to train and test ML models on data from the Solar Dynamics Observatory
- some notebooks for data exploration and results analysis.
It contains all the code supporting the publication:
[Multi-Channel Auto-Calibration for the Atmospheric Imaging Assembly using Machine Learning](https://arxiv.org/abs/2012.14023)
Files
sdo-autocal_pub-master.zip
Files
(4.6 MB)
| Name | Size | Download all |
|---|---|---|
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md5:f79b70d17388047b32f05504a705f0ad
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4.6 MB | Preview Download |
Additional details
Related works
- Is supplement to
- Preprint: arXiv:2012.14023 (arXiv)
- Is supplemented by
- Dataset: 10.5281/zenodo.4430801 (DOI)
- References
- Dataset: 10.3847/1538-4365/ab1005 (DOI)