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Lessons learned from the two largest Galaxy morphological classification catalogues built by convolutional neural networks
T. Y. Cheng*, H. Domínguez Sánchez, J. Vega-Ferrero, C. J. Conselice, M. Siudek, A. Aragón-Salamanca, M. Bernardi, R. Cooke, L. Ferreira, M. Huertas-Company, J. Krywult, A. Palmese, A. Pieres, A. A. Plazas Malagón, A. Carnero Rosell, D. Gruen, D. Thomas, D. Bacon, D. Brooks, D. J. James
*Corresponding author for this work
- Durham University
- Centro de Estudios de Física del Cosmos de Aragón
- CSIC - Instituto de Ciencias del Espacio (ICE)
- Instituto de Astrofísica de Canarias
- University of Manchester
- Institute for High Energy Physics
- University of Nottingham
- University of Pennsylvania
- CNRS
- Jan Kochanowski University in Kielce
- University of California at Berkeley
- Laboratório Interinstitucional de e-Astronomia
- Observatório Nacional
- Princeton University
- University of La Laguna
- Ludwig Maximilian University of Munich
- University College London
- Harvard-Smithsonian Center for Astrophysics
- University of California at Santa Cruz
- University of Illinois at Urbana-Champaign
- Oak Ridge National Laboratory
- CIEMAT
- University of Cambridge
- Fermi National Accelerator Laboratory
- University of Michigan, Ann Arbor
- University of Oslo
- The University of Chicago
- Universidad Autónoma de Madrid
- Ohio State University
- Macquarie University
- Lowell Observatory
- University of Hamburg
- School Of Physics And Astronomy
- University of Southampton
- Lawrence Berkeley National Laboratory
- ICREA
- University of Queensland
- Carnegie Mellon University
- Indian Institute of Technology Hyderabad
- California Institute of Technology
Research output: Contribution to journal › Article › peer-review
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