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Faint Object Classification Using Artificial Neural Networks
Published online by Cambridge University Press: 26 July 2016
Abstract
Artificial Neural Network techniques are applied to the classification of faint objects, detected in digital astronomical images, and a Bayesian classifier (the neural network classifier, NNC hereafter) is proposed. This classifier can be implemented using a feedforward multilayered neural network trained by the back-propagation procedure (Werbos 1974).
- Type
- Part Five: Image Detection, Cataloguing and Classification
- Information
- Symposium - International Astronomical Union , Volume 161: Astronomy from Wide-Field Imaging , 1994 , pp. 249 - 252
- Copyright
- Copyright © Kluwer 1994