On the Performance of Generative Adversarial Network (GAN) Variants: A Clinical Data Study

Jaesung Yoo; Jeman Park; An Wang; David Mohaisen; Joongheon Kim

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arXiv · 2009.09579

On the Performance of Generative Adversarial Network (GAN) Variants: A Clinical Data Study

Jaesung Yoo·Jeman Park·An Wang·David Mohaisen·Joongheon Kim

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Abstract

Generative Adversarial Network (GAN) is a useful type of Neural Networks in various types of applications including generative models and feature extraction. Various types of GANs are being researched with different insights, resulting in a diverse family of GANs with a better performance in each generation. This review focuses on various GANs categorized by their common traits.

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Jaesung Yoo, Jeman Park, An Wang, David Mohaisen, Joongheon Kim. 2020-09-21. On the Performance of Generative Adversarial Network (GAN) Variants: A Clinical Data Study. https://arxiv.org/abs/2009.09579

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