all AI news
Improving Astronomical Time-series Classification via Data Augmentation with Generative Adversarial Networks. (arXiv:2205.06758v1 [astro-ph.IM])
cs.LG updates on arXiv.org arxiv.org
Due to the latest advances in technology, telescopes with significant sky
coverage will produce millions of astronomical alerts per night that must be
classified both rapidly and automatically. Currently, classification consists
of supervised machine learning algorithms whose performance is limited by the
number of existing annotations of astronomical objects and their highly
imbalanced class distributions. In this work, we propose a data augmentation
methodology based on Generative Adversarial Networks (GANs) to generate a
variety of synthetic light curves from variable …
arxiv astro augmentation classification data generative adversarial networks networks series time