Lessons learned from the two largest Galaxy morphological classification catalogues built by convolutional neural networks
We compare the two largest galaxy morphology catalogues, which separate early- and late-type galaxies at intermediate redshift. The two catalogues were built by applying supervised deep learning (convolutional neural networks, CNNs) to the Dark Energy Survey data down to a magnitude limit of ~21 mag. The methodologies used for the construction of
Cheng, T. -Y. et al.
Fecha de publicación:
1
2023