Published June 24, 2022
| Version v1
Journal article
Open
Learning to detect RFI in radio astronomy without seeing it
- 1. University of Amsterdam
- 2. Astron
- 3. University of Amsterdam, Netherlands eScience Centre
- 4. Elena
Description
Dataset for training and evaluating the generative novelty detection-based models used for RFI detection. The LOFAR dataset is made up of the following observations from the LTA:
| Project | Observation ID | Source | Number of sub-bands | Channels per subband | Duration | Date |
| LC9_014 | 629174 | 3C295 | 243 | 16 | 599.0s | 2017-11-21 19:42:02 |
| DDT9_001 | 631961 | 3C380 | 243 | 16 | 599.0s | 2017-12-07 17:12:00 |
| LC9_004 | 632121 | 3C295 | 243 | 16 | 599.0s | 2017-12-12 10:00:00 |
| LC9_005 | 643433 | 3C295 | 243 | 16 | 599.0s | 2018-03-02 05:12:00 |
| LC9_030 | 652366 | 3C295 | 243 | 16 | 599.0s | 2018-05-11 01:46:12 |
For usage details please see the paper's Github repository.
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