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The Ethereal
On the Performance of Generative Adversarial Network (GAN) Variants: A Clinical Data Study
September 21, 2020 ยท Declared Dead ยท ๐ Information and Communication Technology Convergence
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Jaesung Yoo, Jeman Park, An Wang, David Mohaisen, Joongheon Kim
arXiv ID
2009.09579
Category
cs.NE: Neural & Evolutionary
Cross-listed
cs.AI,
cs.LG
Citations
3
Venue
Information and Communication Technology Convergence
Last Checked
4 months ago
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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