Generative Adversarial Networks and Its Applications in Biomedical Informatics

Generative Adversarial Networks and Its Applications in Biomedical Informatics

The basic Generative Adversarial Networks (GAN) model is composed of the input vector, generator, and discriminator. Among them, the generator and discriminator are implicit function expressions, usually implemented by deep neural networks. GAN can learn the generative model of any data distribution...

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Bibliographic Details
Main Authors:	Lan Lan, Lei You, Zeyang Zhang, Zhiwei Fan, Weiling Zhao, Nianyin Zeng, Yidong Chen, Xiaobo Zhou
Format:	Article
Language:	English
Published:	Frontiers Media S.A. 2020-05-01
Series:	Frontiers in Public Health
Subjects:	Generative Adversarial Networks (GAN) generator discriminator data augmentation image conversion biomedical applications
Online Access:	https://www.frontiersin.org/article/10.3389/fpubh.2020.00164/full

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