Multiwavelength classification of X-ray selected galaxy cluster candidates using convolutional neural networks

Matej Kosiba; Maggie Lieu; Bruno Altieri; Nicolas Clerc; Lorenzo Faccioli; Sarah Kendrew; Ivan Valtchanov; Tatyana Sadibekova; Marguerite Pierre; Filip Hroch; Norbert Werner; Luka´s Burget; Christian Garrel; Elias Koulouridis; Evelina Gaynullina; Mona Molham; Miriam E. Ramos-Ceja; Alina Khalikova

doi:10.5281/zenodo.7236582

Published June 17, 2020 | Version v2

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Multiwavelength classification of X-ray selected galaxy cluster candidates using convolutional neural networks

Classification dataset used in Kosiba et al. 2020 (10.1093/mnras/staa1723) consisting of candidate clusters in the XCLASS survey

Training and testing images and corresponding labels low-z (clusters, 0<z<0.3), hi-z (clusters, z>0.3), nearby galaxy, point source (point, double source, star/AGN), and other (artefact, edge)

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Kosiba, M., et al. 2020 (10.1093/mnras/staa1723)
Clerc, N., et al. 2012 (10.1111/j.1365-2966.2012.21153.x)

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Zenodo

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Monthly Notices of the Royal Astronomical Society, 496(4), 4141–4153, 2020.

License: Creative Commons Attribution 4.0 International

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Created: October 21, 2022
Modified: October 22, 2022

Multiwavelength classification of X-ray selected galaxy cluster candidates using convolutional neural networks

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Kosiba2020.zip

Files (259.3 MB)

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