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Convolutional neural networks for transient candidate vetting in large-scale surveys. / Gieseke, Fabian; Bloemen, Steven; van den Bogaard, Cas; Heskes, Tom; Kindler, Jonas; Scalzo, Richard A.; Ribeiro, Valério A. R. M.; van Roestel, Jan; Groot, Paul J.; Yuan, Fang; Möller, Anais; Tucker, Brad E.
In:
Monthly Notices of the Royal Astronomical Society, Vol. 472, No. 3, 12.2017, p. 3101-3114.
Research output: Contribution to journal › Journal article › Research › peer-review
Harvard
Gieseke, F, Bloemen, S, van den Bogaard, C, Heskes, T, Kindler, J, Scalzo, RA, Ribeiro, VARM, van Roestel, J, Groot, PJ, Yuan, F, Möller, A & Tucker, BE 2017, '
Convolutional neural networks for transient candidate vetting in large-scale surveys',
Monthly Notices of the Royal Astronomical Society, vol. 472, no. 3, pp. 3101-3114.
https://doi.org/10.1093/mnras/stx2161APA
Gieseke, F., Bloemen, S., van den Bogaard, C., Heskes, T., Kindler, J., Scalzo, R. A., Ribeiro, V. A. R. M., van Roestel, J., Groot, P. J., Yuan, F., Möller, A., & Tucker, B. E. (2017).
Convolutional neural networks for transient candidate vetting in large-scale surveys.
Monthly Notices of the Royal Astronomical Society,
472(3), 3101-3114.
https://doi.org/10.1093/mnras/stx2161Vancouver
Gieseke F, Bloemen S, van den Bogaard C, Heskes T, Kindler J, Scalzo RA et al.
Convolutional neural networks for transient candidate vetting in large-scale surveys.
Monthly Notices of the Royal Astronomical Society. 2017 Dec;472(3):3101-3114.
https://doi.org/10.1093/mnras/stx2161Author
Gieseke, Fabian ; Bloemen, Steven ; van den Bogaard, Cas ; Heskes, Tom ; Kindler, Jonas ; Scalzo, Richard A. ; Ribeiro, Valério A. R. M. ; van Roestel, Jan ; Groot, Paul J. ; Yuan, Fang ; Möller, Anais ; Tucker, Brad E. / Convolutional neural networks for transient candidate vetting in large-scale surveys. In: Monthly Notices of the Royal Astronomical Society. 2017 ; Vol. 472, No. 3. pp. 3101-3114.
Bibtex
@article{25a9852276b24eb7a3dd5cc54b2b490e,
title = "Convolutional neural networks for transient candidate vetting in large-scale surveys",
keywords = "methods: data analysis, techniques: image processing, surveys, supernovae: general",
author = "Fabian Gieseke and Steven Bloemen and {van den Bogaard}, Cas and Tom Heskes and Jonas Kindler and Scalzo, {Richard A.} and Ribeiro, {Val{\'e}rio A. R. M.} and {van Roestel}, Jan and Groot, {Paul J.} and Fang Yuan and Anais M{\"o}ller and Tucker, {Brad E.}",
year = "2017",
month = dec,
doi = "10.1093/mnras/stx2161",
language = "English",
volume = "472",
pages = "3101--3114",
journal = "Royal Astronomical Society. Monthly Notices",
issn = "0035-8711",
publisher = "Oxford University Press",
number = "3",
}
RIS
TY - JOUR
T1 - Convolutional neural networks for transient candidate vetting in large-scale surveys
AU - Gieseke, Fabian
AU - Bloemen, Steven
AU - van den Bogaard, Cas
AU - Heskes, Tom
AU - Kindler, Jonas
AU - Scalzo, Richard A.
AU - Ribeiro, Valério A. R. M.
AU - van Roestel, Jan
AU - Groot, Paul J.
AU - Yuan, Fang
AU - Möller, Anais
AU - Tucker, Brad E.
PY - 2017/12
Y1 - 2017/12
KW - methods: data analysis
KW - techniques: image processing
KW - surveys
KW - supernovae: general
U2 - 10.1093/mnras/stx2161
DO - 10.1093/mnras/stx2161
M3 - Journal article
VL - 472
SP - 3101
EP - 3114
JO - Royal Astronomical Society. Monthly Notices
JF - Royal Astronomical Society. Monthly Notices
SN - 0035-8711
IS - 3
ER -
