Galaxy Classification by Human Eyes and by Artificial Neural Networks
Abstract
The rapid increase in data on galaxy images at low and high redshift calls for re-examination of the classification schemes and for new automatic objective methods. Here we present a classification method by Artificial Neural Networks. We also show results from a comparative study we carried out using a new sample of 830 APM digitised galaxy images. These galaxy images were classified by 6 experts independently. It is shown that the ANNs can replicate the classification by a human expert almost to the same degree of agreement as that between two human experts, to within 2 -type units. Similar methods can be applied to automatic classification of galaxy spectra. We illustrate it by Principal Component Analysis of galaxy spectra, and discuss future large surveys.
Keywords
Cite
@article{arxiv.astro-ph/9505091,
title = {Galaxy Classification by Human Eyes and by Artificial Neural Networks},
author = {Ofer Lahav},
journal= {arXiv preprint arXiv:astro-ph/9505091},
year = {2007}
}
Comments
review talk in "The World of Galaxies II", Lyon 1994. 13 pages (including 3 figures). Compressed postscript file available by anonymous ftp from ftp://ftp.ast.cam.ac.uk/pub/lahav/lyon/lyon6.ps.Z