On the Performance of Generative Adversarial Network (GAN) Variants: A Clinical Data Study
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Abstract (arXiv)
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.
Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). First posted on arXiv 21 Sep 2020.
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- 2025Synthetic Data Generation for Augmenting Small Samplescited by 3
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