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Machine-learning approaches to exoplanet transit detection and candidate validation in wide-field ground-based surveys

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Schanche, N., Cameron, A. Collier, Hébrard, G., Nielsen, L., Triaud, A. H. M. J., Almenara, J. M., Alsubai, K. A., Anderson, D. R., Armstrong, D. J., Barros, S. C. C. et al.
(2019) Machine-learning approaches to exoplanet transit detection and candidate validation in wide-field ground-based surveys. Monthly Notices of the Royal Astronomical Society, 483 (4). pp. 5534-5547. doi:10.1093/mnras/sty3146

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Official URL: http://dx.doi.org/10.1093/mnras/sty3146

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Item Type: Journal Article
Divisions: Faculty of Science > Physics
Journal or Publication Title: Monthly Notices of the Royal Astronomical Society
Publisher: Wiley
ISSN: 0035-8711
Official Date: March 2019
Dates:
DateEvent
March 2019Published
13 November 2018Accepted
Volume: 483
Number: 4
Page Range: pp. 5534-5547
DOI: 10.1093/mnras/sty3146
Status: Peer Reviewed
Publication Status: Published
Access rights to Published version: Restricted or Subscription Access

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