28 citations · 36 across the 3 of their papers we have counts for
3 papers
Rotation and flipping invariant self-organizing maps with astronomical images: A cookbook and application to the VLA Sky Survey QuickLook images
A. N. Vantyghem, T. J. Galvin, B. Sebastian +12
Modern wide field radio surveys typically detect millions of objects. Techniques based on machine learning are proving to be useful for classifying large numbers of objects. The se…
Estimating Galaxy Redshift in Radio-Selected Datasets using Machine Learning
Kieran J. Luken, Ray P. Norris, Laurence A. F. Park +2
All-sky radio surveys are set to revolutionise the field with new discoveries. However, the vast majority of the tens of millions of radio galaxies won't have the spectroscopic red…
Radio Galaxy Zoo: Knowledge Transfer Using Rotationally Invariant Self-Organising Maps
T. J. Galvin, M. Huynh, R. P. Norris +7
With the advent of large scale surveys the manual analysis and classification of individual radio source morphologies is rendered impossible as existing approaches do not scale. Th…