GAN

Xuliang Yang1,2, Aimin Pan3,4, Rodolfo C Raga2

  • 1University and Urban Integration Development Research Center, Dongguan City University, 523419, Dongguan, China.

Scientific reports
|April 28, 2025
PubMed
概括

本研究介绍了使用生成对抗网络 (GAN) 和视觉转换器 (ViT) 的先进数字人类教育平台. 该平台增强了头像的真实性和交互速度,大大提高了学生的学习成果.

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