180 citations · 436 across the 11 of their papers we have counts for
3 papers · 1 filter
The PAU Survey: Background light estimation with deep learning techniques
Laura Cabayol-Garcia, Martin B. Eriksen, Àlex Alarcón +17
In any imaging survey, measuring accurately the astronomical background light is crucial to obtain good photometry. This paper introduces BKGnet, a deep neural network to predict t…
The PAU Survey: star-galaxy classification with multi narrow-band data
Laura Cabayol, Ignacio Sevilla-Noarbe, Enrique Fernández +18
Classification of stars and galaxies is a well-known astronomical problem that has been treated using different approaches, most of them relying on morphological information. In th…
Photometric redshift analysis in the Dark Energy Survey Science Verification data
C. Sánchez, M. Carrasco Kind, H. Lin +74
We present results from a study of the photometric redshift performance of the Dark Energy Survey (DES), using the early data from a Science Verification (SV) period of observation…