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CASI-2D: Convolutional Approach to Shell Identification - 2D

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Ada Coda
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CASI-2D: Convolutional Approach to Shell Identification - 2D

Postby Ada Coda » Fri May 31, 2019 10:16 pm

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.

Credit: Van Oort, Colin M.; Xu, Duo; Offner, Stella S. R.; Gutermuth, Robert A.

Site: https://gitlab.com/casi-project/casi-2d
https://ui.adsabs.harvard.edu/abs/2019arXiv190509310V

Bibcode: 2019ascl.soft05023V

ID: ascl:1905.023

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