Pushing automated morphological classifications to their limits with the Dark Energy Survey
We present morphological classifications of ~27 million galaxies from the Dark Energy Survey (DES) Data Release 1 (DR1) using a supervised deep learning algorithm. The classification scheme separates: (a) early-type galaxies (ETGs) from late-type galaxies (LTGs); and (b) face-on galaxies from edge-on. Our convolutional neural networks (CNNs) are
Vega-Ferrero, J. et al.
Fecha de publicación:
9
2021