29 citations · 54 across the 3 of their papers we have counts for
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astro-ph.IM2023★ 17 cited
The ROAD to discovery: machine learning-driven anomaly detection in radio astronomy spectrograms
Michael Mesarcik, Albert-Jan Boonstra, Marco Iacobelli +3
As radio telescopes increase in sensitivity and flexibility, so do their complexity and data-rates. For this reason automated system health management approaches are becoming incre…
astro-ph.IM2022★ 29 cited
Learning to detect RFI in radio astronomy without seeing it
Michael Mesarcik, Albert-Jan Boonstra, Elena Ranguelova +1
Radio Frequency Interference (RFI) corrupts astronomical measurements, thus affecting the performance of radio telescopes. To address this problem, supervised segmentation models h…