132 citations · 145 across the 4 of their papers we have counts for
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Infrared bubble recognition in the Milky Way and beyond using deep learning
Shimpei Nishimoto, Toshikazu Onishi, Atsushi Nishimura +9
We propose a deep learning model that can detect Spitzer bubbles accurately using two-wavelength near-infrared data acquired by the Spitzer Space Telescope and JWST. The model is b…
Nobeyama Cygnus-X Survey: Physical Properties of CO clumps in DR-6(W), DR-9 and DR-13S regions
I. Toledano--Juárez, E. de la Fuente, K. Kawata +10
Cygnus-X is considered a region of interest for high-energy astrophysics, since the Cygnus OB2 association has been confirmed as a PeVatron in the Cygnus cocoon. In this research n…
Predicting reliable H column density maps from molecular line data using machine learning
Yoshito Shimajiri, Yasutomo Kawanishi, Shinji Fujita +13
The total mass estimate of molecular clouds suffers from the uncertainty in the H-CO conversion factor, the so-called factor, which is used to convert the C…
Revealing the physical properties of molecular gas in Orion with a large scale survey in J=2-1 lines of 12CO, 13CO and C18O
Atsushi Nishimura, Kazuki Tokuda, Kimihiro Kimura +8
We present fully sampled ~3' resolution images of the 12CO(J=2-1), 13CO(J=2-1), and C18O(J=2-1) emission taken with the newly developed 1.85-m mm-submm telescope toward the entire…