11 citations · 31 across the 7 of their papers we have counts for
4 papers · 1 filter
Observations of DNC and DCO toward the -shaped Filament and Starless Cores in the Orion Molecular Clouds
Ken'ichi Tatematsu, Atsushi Nishimura, Hideo Ogawa +25
Although the deuterium fraction is known to be a powerful evolutionary tracer, its variation within individual molecular cloud cores is still poorly understood. The northern …
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…
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…
Distance determination of molecular clouds in the 1st quadrant of the Galactic plane using deep learning : I. Method and Results
Shinji Fujita, A. M. Ito, Yusuke Miyamoto +15
Machine learning has been successfully applied in varied field but whether it is a viable tool for determining the distance to molecular clouds in the Galaxy is an open question. I…