Search Results for author: V. Amaro

Found 1 papers, 0 papers with code

Photometric redshifts for the Kilo-Degree Survey. Machine-learning analysis with artificial neural networks

no code implementations13 Sep 2017 M. Bilicki, H. Hoekstra, M. J. I. Brown, V. Amaro, C. Blake, S. Cavuoti, J. T. A. de Jong, C. Georgiou, H. Hildebrandt, C. Wolf, A. Amon, M. Brescia, S. Brough, M. V. Costa-Duarte, T. Erben, K. Glazebrook, A. Grado, C. Heymans, T. Jarrett, S. Joudaki, K. Kuijken, G. Longo, N. Napolitano, D. Parkinson, C. Vellucci, G. A. Verdoes Kleijn, L. Wang

The second dataset, optimized for low-redshift studies such as galaxy-galaxy lensing, is limited to r<20, and provides photo-zs of much better quality than in the full-depth case thanks to incorporating optical magnitudes, colours, and sizes in the GAMA-calibrated photo-z derivation.

Cosmology and Nongalactic Astrophysics Astrophysics of Galaxies Instrumentation and Methods for Astrophysics

Cannot find the paper you are looking for? You can Submit a new open access paper.