42 citations · 59 across the 3 of their papers we have counts for
5 papers
A New Task: Deriving Semantic Class Targets for the Physical Sciences
Micah Bowles, Hongming Tang, Eleni Vardoulaki +8
We define deriving semantic class targets as a novel multi-modal task. By doing so, we aim to improve classification schemes in the physical sciences which can be severely abstract…
Structured Variational Inference for Simulating Populations of Radio Galaxies
David J. Bastien, Anna M. M. Scaife, Hongming Tang +2
We present a model for generating postage stamp images of synthetic Fanaroff-Riley Class I and Class II radio galaxies suitable for use in simulations of future radio surveys such…
Attention-gating for improved radio galaxy classification
Micah Bowles, Anna M. M. Scaife, Fiona Porter +2
In this work we introduce attention as a state of the art mechanism for classification of radio galaxies using convolutional neural networks. We present an attention-based model th…
Transfer learning for radio galaxy classification
Hongming Tang, Anna M. M. Scaife, J. P. Leahy
In the context of radio galaxy classification, most state-of-the-art neural network algorithms have been focused on single survey data. The question of whether these trained algori…
Radio Galaxy Zoo: ClaRAN - A Deep Learning Classifier for Radio Morphologies
Chen Wu, O. Ivy Wong, Lawrence Rudnick +13
The upcoming next-generation large area radio continuum surveys can expect tens of millions of radio sources, rendering the traditional method for radio morphology classification t…