Photometric redshift estimation via deep learning. Generalized and pre-classification-less, image based, fully probabilistic redshifts

Abstract:
No abstract specified

SEEK ID: https://publications.h-its.org/publications/205

DOI: 10.1051/0004-6361/201731326

Research Groups: Astroinformatics

Publication type: Journal

Journal: Astronomy & Astrophysics

Citation: A&A 609:A111

Date Published: 2018

Registered Mode: imported from a bibtex file

Citation
D’Isanto, A., & Polsterer, K. L. (2018). Photometric redshift estimation via deep learning. In Astronomy & Astrophysics (Vol. 609, p. A111). EDP Sciences. https://doi.org/10.1051/0004-6361/201731326
Activity

Views: 6400

Created: 7th Sep 2019 at 10:22

Last updated: 5th Mar 2024 at 21:23

help Tags

This item has not yet been tagged.

help Attributions

None

Powered by
(v.1.15.2)
Copyright © 2008 - 2024 The University of Manchester and HITS gGmbH