… neural networks. In Section 3 we discuss the data provided from Radio Galaxy Zoo, the minor
pre-… 1 (DR1; Wong et al., in preparation) of the citizen science project Radio Galaxy Zoo. …

… , 1 deep learning-based method known as Classifying Radio sources Automatically using
Neural networks (… Claran takes as input a pair of World Coordinate System-aligned radio and …

… We also show that training our method on Radio Galaxy Zoo cross-identifications gives
comparable results to training on expert cross-identifications, demonstrating the value of …

… , classifying a radio galaxy as a GRG requires astronomers to (i) identify radio components
… radio maps; (iii) find the corresponding host galaxy of the DRAGN; (iv) measure the host …

… Radio Galaxy Zoo (RGZ) data set image features which can be applied to new radio survey
data. … towards automated techniques such as machine learning with neural networks (NNs). …

… In this work, we create a machine learning data set from the RGZ DR1 catalogue … the Radio
Galaxy Zoo Project. The data in this paper are the result of the efforts of the Radio Galaxy Zoo …

… unknown giant radio galaxies (GRGs) using Data Release 1 of the Radio Galaxy Zoo citizen
… the training and validation of deep learning algorithms for new radio surveys. We associate …

… Radio Galaxy Zoo Project. The data in this paper are the result of the efforts of the Radio
Galaxy Zoo … This work makes use of the MiraBest machine learning data set, which is publicly …

… in the Galaxy Zoo Project. The data in this paper are the result of the efforts of the Radio
Galaxy Zoo … Their efforts are individually acknowledged at http://rgzauthors.galaxyzoo.org. …

… have a broader and deeper search-space. The Kaggle Galaxy Zoo competition presented
the challenge of writing an algorithm to find the probability that a galaxy belongs in a particular …