most citedDeep learning denoising by dimension reduction: Application to the ORION-B line cubes

16 citations · 16 across the 1 of their papers we have counts for

collaborators

1 paper

astro-ph.IM2023★ 16 cited

Deep learning denoising by dimension reduction: Application to the ORION-B line cubes

Lucas Einig, Jérôme Pety, Antoine Roueff +29

Context. The availability of large bandwidth receivers for millimeter radio telescopes allows the acquisition of position-position-frequency data cubes over a wide field of view an…