Radio Frequency Interference (RFI), radio signals from electronics, permeates through astronomical observations using radio telescopes. The interference results in lower sensitivity and higher noise when present. Existing methods, such as TFCrop and RFlag, flag RFI to prevent the contamination of observations. However, these approaches are partially automatic and require manual input to flag RFI. We explore artificial intelligence methods using Meta’s Segment Anything Model (SAM) and its parameter space in segmenting RFI. We have developed an open-source pipeline called
This content will become publicly available on March 1, 2025
- PAR ID:
- 10502100
- Publisher / Repository:
- MDPI
- Date Published:
- Journal Name:
- Remote Sensing
- Volume:
- 16
- Issue:
- 5
- ISSN:
- 2072-4292
- Page Range / eLocation ID:
- 797
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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