Star-galaxy separation with a neural network. 2: Multiple Schmidt plate fields

Details Star-galaxy separation with a neural network. 2: Multiple Schmidt plate fields Star-galaxy separation with a neural network. 2: Multiple Schmidt plate fields

Nov 1993

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=1993pasp..105.1354o&link_type=abstract

Astronomical Society of the Pacific, Publications (ISSN 0004-6280), vol. 105, no. 693, p. 1354-1365

Statistics

Methodology

36

Galaxies, Image Classification, Methodology, Neural Nets, Schmidt Cameras, Stars, Accuracy, Comparison, Performance Tests, Sky Surveys (Astronomy)

Scientific paper

A two-color survey of nine fields of the first-epoch Palomar Sky Survey, centered on the North Galactic Pole, has been performed with the Minnesota Automated Plate Scanner (APS). A set of neural network image classifiers are used to perform star-galaxy discrimination automatically to an imposed O magnitude limit of 20.0. We assess the efficiency of image classification and sample completeness through comparisons with a variety of independent studies of the NGP area.

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