Automatic approach to solve the morphological galaxy classification problem using the sparse representation technique and dictionary learning-Reference-Cited by-同舟云学术

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Automatic approach to solve the morphological galaxy classification problem using the sparse representation technique and dictionary learning

Published:2016-04-08 Issue:3 Volume:41 Page:409-426
ISSN:0922-6435
Container-title:Experimental Astronomy
language:en
Short-container-title:Exp Astron

Author:

Diaz-Hernandez R.,Ortiz-Esquivel A.,Peregrina-Barreto H.,Altamirano-Robles L.,Gonzalez-Bernal J.

Publisher

Springer Science and Business Media LLC

Subject

Space and Planetary Science,Astronomy and Astrophysics

Link

http://link.springer.com/content/pdf/10.1007/s10686-016-9495-0.pdf

Reference30 articles.

1. Abraham, R.G., Van Den Bergh, S., Nair, P.: A new approach to galaxy morphology. i. analysis of the sloan digital sky survey early data release. Astrophys. J. 588(1), 218 (2003)

2. Aharon, M., Elad, M., Bruckstein, A.: K-svd: An algorithm for designing overcomplete dictionaries for sparse representation. IEEE Transactions on Signal Processing 54(11), 4311–4322 (2006)

3. Ball, N.M., Loveday, J., Fukugita, M., Nakamura, O., Okamura, S., Brinkmann, J., Brunner, R.J.: Galaxy types in the sloan digital sky survey using supervised artificial neural networks. Mon. Not. R. Astron. Soc. 348(3), 1038–1046 (2004)

4. Bazell, D.: Feature relevance in morphological galaxy classification. Mon. Not. R. Astron. Soc. 316(3), 519–528 (2000)

5. Bazell, D., Aha, D.W.: Ensembles of classifiers for morphological galaxy classification. Astrophys. J. 548(1), 219–223 (2001)

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