Anomaly detection in Hyper Suprime-Cam galaxy images with generative adversarial networks
The problem of anomaly detection in astronomical surveys is becoming increasingly important as data sets grow in size. We present the results of an unsupervised anomaly detection method using a Wasserstein generative adversarial network (WGAN) on nearly one million optical galaxy images in the Hyper Suprime-Cam (HSC) survey. The WGAN learns to
Storey-Fisher, Kate et al.
Fecha de publicación:
12
2021