Detecting Solar system objects with convolutional neural networks Article Swipe
Maggie Lieu
,
L. Conversi
,
B. Altieri
,
B. Carry
·
YOU?
·
· 2019
· Open Access
·
· DOI: https://doi.org/10.1093/mnras/stz761
YOU?
·
· 2019
· Open Access
·
· DOI: https://doi.org/10.1093/mnras/stz761
In the preparation for ESA's Euclid mission and the large amount of data it will produce, we train deep convolutional neural networks on Euclid simulations classify solar system objects from other astronomical sources. Using transfer learning we are able to achieve a good performance despite our tiny dataset with as few as 7512 images. Our best model correctly identifies objects with a top accuracy of 94% and improves to 96% when Euclid's dither information is included. The neural network misses ~50% of the slowest moving asteroids (v < 10 arcsec/h) but is otherwise able to correctly classify asteroids even down to 26 mag. We show that the same model also performs well at classifying stars, galaxies and cosmic rays, and could potentially be applied to distinguish all types of objects in the Euclid data and other large optical surveys.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1093/mnras/stz761
- OA Status
- green
- Cited By
- 39
- References
- 55
- Related Works
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- OpenAlex ID
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All OpenAlex metadata
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https://openalex.org/W2883728770Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1093/mnras/stz761Digital Object Identifier
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Detecting Solar system objects with convolutional neural networksWork title
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articleOpenAlex work type
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enPrimary language
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2019Year of publication
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2019-03-13Full publication date if available
- Authors
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Maggie Lieu, L. Conversi, B. Altieri, B. CarryList of authors in order
- Landing page
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https://doi.org/10.1093/mnras/stz761Publisher landing page
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YesWhether a free full text is available
- OA status
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greenOpen access status per OpenAlex
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https://arxiv.org/pdf/1807.10912Direct OA link when available
- Concepts
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Physics, Convolutional neural network, Asteroid, Dither, Artificial neural network, Galaxy, Stars, Artificial intelligence, COSMIC cancer database, Solar System, Astronomy, Astrophysics, Pattern recognition (psychology), Computer vision, Computer science, Noise shapingTop concepts (fields/topics) attached by OpenAlex
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39Total citation count in OpenAlex
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2025: 9, 2024: 3, 2023: 8, 2022: 4, 2021: 5Per-year citation counts (last 5 years)
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10Other works algorithmically related by OpenAlex
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