Rotation-invariant convolutional neural networks for galaxy morphology prediction

Monthly Notices of the Royal Astronomical Society

Volumn 450, Issue 2, 2015, Pages 1441-1459

  Dieleman, Sander ^a   Willett, Kyle W ^b   Dambre, Joni ^a  

^a GHENT UNIVERSITY   (Belgium)

^b University of Minnesota   (United States)

Author keywords

Catalogues; Galaxies: general; Methods: data analysis; Techniques: image processing

Indexed keywords

COMPETITION; DEEP NEURAL NETWORKS; IMAGE ANALYSIS; IMAGE CLASSIFICATION; MORPHOLOGY; SURVEYS;

CATALOG; CONVOLUTIONAL NEURAL NETWORK; FORMATION AND EVOLUTIONS; GALAXIES GENERAL; METHODS. DATA ANALYSIS; MORPHOLOGICAL PARAMETERS; MORPHOLOGY CLASSIFICATION; ROTATION INVARIANT; SLOAN DIGITAL SKY SURVEY; TECHNIQUES: IMAGE PROCESSING;

GALAXIES;

EID: 84936124348     PISSN: 00358711     EISSN: 13652966     Source Type: Journal    
DOI: 10.1093/mnras/stv632     Document Type: Article

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