DeepGhostBusters: Using Mask R-CNN to detect and mask ghosting and scattered-light artifacts from optical survey images

Discovering New Strong Gravitational Lenses in the DESI Legacy Imaging Surveys

(2021) X. Huang et al.   ASTROPHYSICAL JOURNAL

Dark Energy Survey Year 3 Results: Photometric Data Set for Cosmology

(2021) I. Sevilla-Noarbe et al.   ASTROPHYSICAL JOURNAL SUPPLEMENT SERIES

DeepShadows: Separating low surface brightness galaxies from artifacts using deep learning

(2021) D. Tanoglidis et al.   Astronomy and Computing

Galactic cirri in deep optical imaging

(2020) Javier Román et al.   ASTRONOMY & ASTROPHYSICS

Using Convolutional Neural Networks to identify Gravitational Lenses in Astronomical images

(2019) Andrew Davies et al.   MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY

Deep learning at scale for the construction of galaxy catalogs in the Dark Energy Survey

(2019) Asad Khan et al.   PHYSICS LETTERS B

Deblending and classifying astronomical sources with Mask R-CNN deep learning

(2019) Colin J Burke et al.   MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY

MAXIMASK and MAXITRACK: Two new tools for identifying contaminants in astronomical images using convolutional neural networks

(2019) M. Paillassa et al.   ASTRONOMY & ASTROPHYSICS

Galaxy detection and identification using deep learning and data augmentation

(2018) R.E. González et al.   Astronomy and Computing

Transfer learning for galaxy morphology from one survey to another

(2018) H Domínguez Sánchez et al.   MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY

CMU DeepLens: deep learning for automatic image-based galaxy–galaxy strong lens finding

(2017) François Lanusse et al.   MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY

The Dark Energy Survey: more than dark energy – an overview

(2016)   MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY

Star–galaxy classification using deep convolutional neural networks

(2016) Edward J. Kim et al.   MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY

Crowdsourcing quality control for Dark Energy Survey images

(2016) P. Melchior et al.   Astronomy and Computing

Detection and removal of artifacts in astronomical images

(2016) S. Desai et al.   Astronomy and Computing

Rotation-invariant convolutional neural networks for galaxy morphology prediction

(2015) Sander Dieleman et al.   MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY

Ultra–Low Surface Brightness Imaging with the Dragonfly Telephoto Array

(2013) Roberto G. Abraham et al.   PUBLICATIONS OF THE ASTRONOMICAL SOCIETY OF THE PACIFIC

Removing Internal Reflections from Deep Imaging Data Sets

(2009) Colin T. Slater et al.   PUBLICATIONS OF THE ASTRONOMICAL SOCIETY OF THE PACIFIC