19 citations · 19 across the 1 of their papers we have counts for
4 papers
Galaxy Zoo: Probabilistic Morphology through Bayesian CNNs and Active Learning
Mike Walmsley, Lewis Smith, Chris Lintott +10
We use Bayesian convolutional neural networks and a novel generative model of Galaxy Zoo volunteer responses to infer posteriors for the visual morphology of galaxies. Bayesian CNN…
The Effect of Minor and Major Mergers on the Evolution of Low Excitation Radio Galaxies
Yjan A. Gordon, Kevin A. Pimbblet, Sugata Kaviraj +8
We use deep, , -band imaging from the Dark Energy Camera Legacy Survey (DECaLS) to search for past, or ongoing, merger activit…
Modeling with the Crowd: Optimizing the Human-Machine Partnership with Zooniverse
Hugh Dickinson, Lucy Fortson, Claudia Scarlata +2
LSST and Euclid must address the daunting challenge of analyzing the unprecedented volumes of imaging and spectroscopic data that these next-generation instruments will generate. A…
Identification of Low Surface Brightness Tidal Features in Galaxies Using Convolutional Neural Networks
Mike Walmsley, Annette M. N. Ferguson, Robert G. Mann +1
Faint tidal features around galaxies record their merger and interaction histories over cosmic time. Due to their low surface brightnesses and complex morphologies, existing automa…