69 citations · 92 across the 6 of their papers we have counts for
6 papers
Radio Galaxy Zoo: Leveraging latent space representations from variational autoencoder
Sambatra Andrianomena, Hongming Tang
We propose to learn latent space representations of radio galaxies, and train a very deep variational autoencoder (\protect\Verb+VDVAE+) on RGZ DR1, an unlabeled dataset, to this e…
The LOFAR Two-Metre Sky Survey (LoTSS): VI. Optical identifications for the second data release
M. J. Hardcastle, M. A. Horton, W. L. Williams +49
The second data release of the LOFAR Two-Metre Sky Survey (LoTSS) covers 27% of the northern sky, with a total area of deg. The high angular resolution of LOFAR wi…
Hydra II: Characterisation of Aegean, Caesar, ProFound, PyBDSF, and Selavy source finders
M. M. Boyce, A. M. Hopkins, S. Riggi +24
We present a comparison between the performance of a selection of source finders using a new software tool called Hydra. The companion paper, Paper~I, introduced the Hydra tool and…
Hydra I: An extensible multi-source-finder comparison and cataloguing tool
M. M. Boyce, A. M. Hopkins, S. Riggi +24
The latest generation of radio surveys are now producing sky survey images containing many millions of radio sources. In this context it is highly desirable to understand the perfo…
Radio Galaxy Zoo EMU: Towards a Semantic Radio Galaxy Morphology Taxonomy
Micah Bowles, Hongming Tang, Eleni Vardoulaki +20
We present a novel natural language processing (NLP) approach to deriving plain English descriptors for science cases otherwise restricted by obfuscating technical terminology. We…
Radio Galaxy Zoo: Giant Radio Galaxy Classification using Multi-Domain Deep Learning
H. Tang, A. M. M. Scaife, O. I. Wong +1
In this work, we explore the potential of multi-domain multi-branch convolutional neural networks (CNNs) for identifying comparatively rare giant radio galaxies from large volumes…