Using an artificial neural network to classify multicomponent emission lines 
with integral field spectroscopy from SAMI and S7

Hampton, E. J.; Medling, A. M.; Groves, B.; Kewley, L.; Dopita, M.; Davies, R.; Ho, I.-T.; Kaasinen, M.; Leslie, S.; Sharp, R.; Sweet, S. M.; Thomas, A. D.; Allen, J.; Bland-Hawthorn, J.; Brough, S.; Bryant, J. J.; Croom, S.; Goodwin, M.; Green, A.; Konstantantopoulos, I. S.; Lawrence, J.; López-Sánchez, Á. R.; Lorente, N. P. F.; McElroy, R.; Owers, M. S.; Richards, S. N.; Shastri, P.

doi:10.1093/mnras/stx1413

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Using an artificial neural network to classify multicomponent emission lines with integral field spectroscopy from SAMI and S7

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Davies, R.
Infrared and Submillimeter Astronomy, MPI for Extraterrestrial Physics, Max Planck Society;

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Hampton, E. J., Medling, A. M., Groves, B., Kewley, L., Dopita, M., Davies, R., et al. (2017). Using an artificial neural network to classify multicomponent emission lines with integral field spectroscopy from SAMI and S7. Monthly Notices of the Royal Astronomical Society, 470(3), 3395-3416. doi:10.1093/mnras/stx1413.

Cite as: https://hdl.handle.net/11858/00-001M-0000-002D-D43C-C

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