201 citations · 647 across the 31 of their papers we have counts for
4 papers · 1 filter
Quantifying the Poor Purity and Completeness of Morphological Samples Selected by Galaxy Colour
Rebecca J. Smethurst, Karen L. Masters, Brooke D. Simmons +7
The galaxy population is strongly bimodal in both colour and morphology, and the two measures correlate strongly, with most blue galaxies being late-types (spirals) and most early-…
Practical Galaxy Morphology Tools from Deep Supervised Representation Learning
Mike Walmsley, Anna M. M. Scaife, Chris Lintott +9
Astronomers have typically set out to solve supervised machine learning problems by creating their own representations from scratch. We show that deep learning models trained to an…
Revisiting Citizen Science Through the Lens of Hybrid Intelligence
Janet Rafner, Miroslav Gajdacz, Gitte Kragh +13
Artificial Intelligence (AI) can augment and sometimes even replace human cognition. Inspired by efforts to value human agency alongside productivity, we discuss the benefits of so…
Galaxy Zoo DECaLS: Detailed Visual Morphology Measurements from Volunteers and Deep Learning for 314,000 Galaxies
Mike Walmsley, Chris Lintott, Tobias Geron +15
We present Galaxy Zoo DECaLS: detailed visual morphological classifications for Dark Energy Camera Legacy Survey images of galaxies within the SDSS DR8 footprint. Deeper DECaLS ima…