Automated galaxy classification using artificial neural networks

Steve C. Odewahn

doi:10.1117/12.279549

30 October 1997 Automated galaxy classification using artificial neural networks

Steve C. Odewahn

Proceedings Volume 3164, Applications of Digital Image Processing XX; (1997) https://doi.org/10.1117/12.279549
Event: Optical Science, Engineering and Instrumentation '97, 1997, San Diego, CA, United States

Abstract

Current efforts to perform automatic galaxy classification using artificial neural network image classifiers are reviewed. For both digitized photographic Schmidt plate data and newly obtained WFPC2 imagery from the Hubble Space Telescope, a variety of 2D photometric parameter space produce a segregation of Hubble types. Through the use of hidden node layers. a neural network is capable of mapping complicated, highly nonlinear data space. This powerful technique is used to map a multivariate photometric parameter space to the revised Hubble system of galaxy classification.

Citation Download Citation

Steve C. Odewahn "Automated galaxy classification using artificial neural networks", Proc. SPIE 3164, Applications of Digital Image Processing XX, (30 October 1997); https://doi.org/10.1117/12.279549

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