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On Improving the Performance of Glitch Classification for Gravitational Wave Detection by using Generative Adversarial Networks. (arXiv:2207.04001v1 [astro-ph.HE])
cs.LG updates on arXiv.org arxiv.org
Spectrogram classification plays an important role in analyzing gravitational
wave data. In this paper, we propose a framework to improve the classification
performance by using Generative Adversarial Networks (GANs). As substantial
efforts and expertise are required to annotate spectrograms, the number of
training examples is very limited. However, it is well known that deep networks
can perform well only when the sample size of the training set is sufficiently
large. Furthermore, the imbalanced sample sizes in different classes can also …
arxiv astro classification detection generative adversarial networks glitch networks performance