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Data Augmentation Using GANs

Published in arXiv (Cornell University) • Apr 19, 2019
NobleIDNI1P85W64R31S59
Authors:
Fabio Henrique Kiyoiti dos Santos Tanaka
,
Claus Aranha

Abstract

In this paper we propose the use of Generative Adversarial Networks (GAN) to generate artificial training data for machine learning tasks. The generation of artificial training data can be extremely useful in situations such as imbalanced data sets, performing a role similar to SMOTE or ADASYN. It i...

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