Generative Adversarial Networks and Its Applications in Biomedical Informatics.
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ABSTRACT:
SUBMITTER: Lan L
PROVIDER: S-EPMC7235323 | biostudies-literature | 2020
REPOSITORIES: biostudies-literature
Publications
Generative Adversarial Networks and Its Applications in Biomedical Informatics.
Lan Lan L You Lei L Zhang Zeyang Z Fan Zhiwei Z Zhao Weiling W Zeng Nianyin N Chen Yidong Y Zhou Xiaobo X
Frontiers in public health 20200512
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 through adversarial methods with excellent performance. It has been widely applied to different areas since it was proposed in 2014. In this review, we introduced the origin, specific working princip ...[more]
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