91 citations · 184 across the 3 of their papers we have counts for
3 papers
astro-ph.GA2019★ 84 cited
Galaxy morphological classification in deep-wide surveys via unsupervised machine learning
Garreth Martin, Sugata Kaviraj, Alex Hocking +2
Galaxy morphology is a fundamental quantity, that is essential not only for the full spectrum of galaxy-evolution studies, but also for a plethora of science in observational cosmo…
astro-ph.IM2017★ 91 cited
An automatic taxonomy of galaxy morphology using unsupervised machine learning
Alex Hocking, James E. Geach, Yi Sun +1
We present an unsupervised machine learning technique that automatically segments and labels galaxies in astronomical imaging surveys using only pixel data. Distinct from previous…
astro-ph.IM2015★ 9 cited
Teaching a machine to see: unsupervised image segmentation and categorisation using growing neural gas and hierarchical clustering
Alex Hocking, James E. Geach, Neil Davey +1
We present a novel unsupervised learning approach to automatically segment and label images in astronomical surveys. Automation of this procedure will be essential as next-generati…