Search Results for author: Kyle W. Willett

Found 2 papers, 2 papers with code

Galaxy Zoo DECaLS: Detailed Visual Morphology Measurements from Volunteers and Deep Learning for 314,000 Galaxies

1 code implementation16 Feb 2021 Mike Walmsley, Chris Lintott, Tobias Geron, Sandor Kruk, Coleman Krawczyk, Kyle W. Willett, Steven Bamford, Lee S. Kelvin, Lucy Fortson, Yarin Gal, William Keel, Karen L. Masters, Vihang Mehta, Brooke D. Simmons, Rebecca Smethurst, Lewis Smith, Elisabeth M. Baeten, Christine Macmillan

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.

Rotation-invariant convolutional neural networks for galaxy morphology prediction

2 code implementations24 Mar 2015 Sander Dieleman, Kyle W. Willett, Joni Dambre

Unfortunately, even this approach does not scale well enough to keep up with the increasing availability of galaxy images.

General Classification Morphological Analysis +1

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