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The Milky Way project: Leveraging citizen science and machine learning to detect interstellar bubbles

Abstract:

We present Brut, an algorithm to identify bubbles in infrared images of the Galactic midplane. Brut is based on the Random Forest algorithm, and uses bubbles identified by >35,000 citizen scientists from the Milky Way Project to discover the identifying characteristics of bubbles in images from the Spitzer Space Telescope. We demonstrate that Brut's ability to identify bubbles is comparable to expert astronomers. We use Brut to re-assess the bubbles in the Milky Way Project catalog, and fi...

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Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1088/0067-0049/214/1/3

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Institution:
University of Oxford
Division:
MPLS
Department:
Physics
Sub department:
Astrophysics
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Physics
Role:
Author
Publisher:
Institute of Physics Publisher's website
Journal:
Astrophysical Journal Supplement Series Journal website
Volume:
214
Issue:
1
Pages:
3-3
Publication date:
2014-09-01
Acceptance date:
2014-06-07
DOI:
EISSN:
1538-4365
ISSN:
0067-0049
Keywords:
Pubs id:
pubs:481433
UUID:
uuid:62ab04e9-f510-4d3d-b7af-7b8336b25532
Local pid:
pubs:481433
Source identifiers:
481433
Deposit date:
2014-08-27

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