30 citations · 35 across the 3 of their papers we have counts for
4 papers
Using cGANs for Anomaly Detection: Identifying Astronomical Anomalies in JWST NIRcam Imaging
Ruby Pearce-Casey, Hugh Dickinson, Stephen Serjeant +1
We present a proof of concept for mining JWST imaging data for anomalous galaxy populations using a conditional Generative Adversarial Network (cGAN). We train our model to predict…
Rapid prediction of lab-grown tissue properties using deep learning
Allison E. Andrews, Hugh Dickinson, James P. Hague
The interactions between cells and the extracellular matrix are vital for the self-organisation of tissues. In this paper we present proof-of-concept to use machine learning tools…
Galaxy Zoo: Clump Scout -- Design and first application of a two-dimensional aggregation tool for citizen science
Hugh Dickinson, Dominic Adams, Vihang Mehta +9
Galaxy Zoo: Clump Scout is a web-based citizen science project designed to identify and spatially locate giant star forming clumps in galaxies that were imaged by the Sloan Digital…
Detecting gravitational lenses using machine learning: exploring interpretability and sensitivity to rare lensing configurations
Joshua Wilde, Stephen Serjeant, Jane M. Bromley +3
Forthcoming large imaging surveys such as Euclid and the Vera Rubin Observatory Legacy Survey of Space and Time are expected to find more than strong gravitational lens syst…