Galaxy Morphological Classification Catalogue of the Dark Energy Survey Year 3 data with Convolutional Neural Networks
(2021)
Journal Article
Cheng, T.-Y., Conselice, C. J., Aragón-Salamanca, A., Aguena, M., Allam, S., Andrade-Oliveira, F., Annis, J., Bluck, A. F. L., Brooks, D., Burke, D. L., Kind, M. C., Carretero, J., Choi, A., Costanzi, M., da Costa, L. N., Pereira, M. E. S., De Vicente, J., Diehl, H. T., Drlica-Wagner, A., Eckert, K., …To, C. (2021). Galaxy Morphological Classification Catalogue of the Dark Energy Survey Year 3 data with Convolutional Neural Networks. Monthly Notices of the Royal Astronomical Society, 507(3), 4425-4444. https://doi.org/10.1093/mnras/stab2142
We present in this paper one of the largest galaxy morphological classification catalogues to date, including over 20 million of galaxies, using the Dark Energy Survey (DES) Year 3 data based on Convolutional Neural Networks (CNN). Monochromatic i-ba... Read More about Galaxy Morphological Classification Catalogue of the Dark Energy Survey Year 3 data with Convolutional Neural Networks.