Galaxy Zoo DECaLS: Detailed Visual Morphology Measurements from
  Volunteers and Deep Learning for 314,000 Galaxies
  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 images (r=23.6 vs. r=22.2 from SDSS) reveal spiral
arms, weak bars, and tidal features not previously visible in SDSS imaging. To
best exploit the greater depth of DECaLS images, volunteers select from a new
set of answers designed to improve our sensitivity to mergers and bars. Galaxy
Zoo volunteers provide 7.5 million individual classifications over 314,000
galaxies. 140,000 galaxies receive at least 30 classifications, sufficient to
accurately measure detailed morphology like bars, and the remainder receive
approximately 5. All classifications are used to train an ensemble of Bayesian
convolutional neural networks (a state-of-the-art deep learning method) to
predict posteriors for the detailed morphology of all 314,000 galaxies. When
measured against confident volunteer classifications, the networks are
approximately 99% accurate on every question. Morphology is a fundamental
feature of every galaxy; our human and machine classifications are an accurate
and detailed resource for understanding how galaxies evolve.
