Advanced R-GAN: Generating anomaly data for improved detection in imbalanced datasets using regularized generative adversarial network

Today's article comes from the Alexandria Engineering Journal. The authors are Lee et al., from Chung-Ang University, in South Korea. In this paper they showcase a new way that you can balance lopsided datasets when you're training a model.

DOI: 10.1016/j.aej.2024.10.084