CASI-2D: Convolutional Approach to Shell Identification - 2D
Abstract
CASI-2D (Convolutional Approach to Shell Identification) identifies stellar feedback signatures using data from magneto-hydrodynamic simulations of turbulent molecular clouds with embedded stellar sources and deep learning techniques. Specifically, a deep neural network is applied to dense regression and segmentation on simulated density and synthetic 12 CO observations to identify shells, sometimes referred to as "bubbles," and other structures of interest in molecular cloud data.
- Publication:
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Astrophysics Source Code Library
- Pub Date:
- May 2019
- Bibcode:
- 2019ascl.soft05023V
- Keywords:
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- Software