49 citations · 83 across the 10 of their papers we have counts for
4 papers · 1 filter
Radio Galaxy Zoo: EMU -- paving the way for EMU cataloging using AI and citizen science
Hongming Tang, Eleni Vardoulaki, RGZ EMU collaboration
The Evolutionary Map of the Universe (EMU) survey with ASKAP is transforming our understanding of radio galaxies, AGN duty cycles, and cosmic structure. EMUCAT efficiently identifi…
Category-based Galaxy Image Generation via Diffusion Models
Xingzhong Fan, Hongming Tang, Yue Zeng +2
Conventional galaxy generation methods rely on semi-analytical models and hydrodynamic simulations, which are highly dependent on physical assumptions and parameter tuning. In cont…
A model local interpretation routine for deep learning based radio galaxy classification
Hongming Tang, Shiyu Yue, Zijun Wang +5
Radio galaxy morphological classification is one of the critical steps when producing source catalogues for large-scale radio continuum surveys. While many recent studies attempted…
Identifying anomalous radio sources in the EMU Pilot Survey using a complexity-based approach
Gary Segal, David Parkinson, Ray Norris +12
The Evolutionary Map of the Universe (EMU) large-area radio continuum survey will detect tens of millions of radio galaxies, giving an opportunity for the detection of previously u…