Semi-Supervised Learning Based on Generative Adversarial Network: A Comparison Between Good GAN and Bad GAN Approach

Cite

Text

Li et al. "Semi-Supervised Learning Based on Generative Adversarial Network: A Comparison Between Good GAN and Bad GAN Approach." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2019.

Markdown

[Li et al. "Semi-Supervised Learning Based on Generative Adversarial Network: A Comparison Between Good GAN and Bad GAN Approach." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2019.](https://mlanthology.org/cvprw/2019/li2019cvprw-semisupervised/)

BibTeX

@inproceedings{li2019cvprw-semisupervised,
  title     = {{Semi-Supervised Learning Based on Generative Adversarial Network: A Comparison Between Good GAN and Bad GAN Approach}},
  author    = {Li, Wenyuan and Wang, Zichen and Li, Jiayun and Polson, Jennifer and Speier, William and Arnold, Corey W.},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops},
  year      = {2019},
  url       = {https://mlanthology.org/cvprw/2019/li2019cvprw-semisupervised/}
}