248 citations · 331 across the 4 of their papers we have counts for
4 papers
The miniJPAS survey quasar selection II: Machine learning classification with photometric measurements and uncertainties
Natália V. N. Rodrigues, L. Raul Abramo, Carolina Queiroz +23
Astrophysical surveys rely heavily on the classification of sources as stars, galaxies or quasars from multi-band photometry. Surveys in narrow-band filters allow for greater discr…
TOPz: Photometric redshifts for J-PAS
J. Laur, E. Tempel, A. Tamm +30
The importance of photometric galaxy redshift estimation is rapidly increasing with the development of specialised powerful observational facilities. We develop a new photometric r…
The miniJPAS survey: star-galaxy classification using machine learning
P. O. Baqui, V. Marra, L. Casarini +31
Future astrophysical surveys such as J-PAS will produce very large datasets, which will require the deployment of accurate and efficient Machine Learning (ML) methods. In this work…
J-PLUS: The Javalambre Photometric Local Universe Survey
A. J. Cenarro, M. Moles, D. Cristóbal-Hornillos +119
J-PLUS is an ongoing 12-band photometric optical survey, observing thousands of square degrees of the Northern hemisphere from the dedicated JAST/T80 telescope at the Observatorio…