Generative Adversarial Networks and Its Applications in Biomedical Informatics

• Published in: Frontiers in public health Vol. 8; p. 164
• Main Authors: Lan, Lan, You, Lei, Zhang, Zeyang, Fan, Zhiwei, Zhao, Weiling, Zeng, Nianyin, Chen, Yidong, Zhou, Xiaobo
• Format: Journal Article
• Language: English
• Published: Switzerland Frontiers Media S.A 12.05.2020
• Subjects: biomedical applications; Computational Biology; data augmentation; discriminator; Generative Adversarial Networks (GAN); generator; image conversion; Image Processing, Computer-Assisted; Medical Informatics; Neural Networks, Computer; Public Health; generator; data augmentation; image conversion; Generative Adversarial Networks (GAN); biomedical applications; discriminator

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...