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Star-Galaxy Separation with a Neural Network. II. Multiple Schmidt Plate Fields
S. C. Odewahn, R. M. Humphreys, G. Aldering and P. Thurmes
Publications of the Astronomical Society of the Pacific
Vol. 105, No. 693 (1993 November), pp. 1354-1365
Published by: Astronomical Society of the Pacific
Stable URL: http://www.jstor.org/stable/40680198
Page Count: 12
You can always find the topics here!Topics: Image classification, Astronomical objects, Diameters, Artificial neural networks, Galaxies, Astronomical magnitude, Area surveys, Images, Image processing, Stars
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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. 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.
Publications of the Astronomical Society of the Pacific © 1993 The University of Chicago Press