Galaxy Classification by Human Eyes and by Artificial Neural Networks

dc.creatorLahav, Ofer
dc.date1995-05-19
dc.date.accessioned2026-07-25T12:41:08Z
dc.descriptionThe 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 $T$-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.
dc.descriptionreview 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
dc.identifierhttps://arxiv.org/abs/astro-ph/9505091
dc.identifierhttp://arxiv.org/abs/astro-ph/9505091
dc.identifier.urihttps://dspace.dare.co.zw/handle/123456789/11144
dc.subjectAstrophysics
dc.titleGalaxy Classification by Human Eyes and by Artificial Neural Networks
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