Data Balancing using Deep Convolutional Generative Adversarial Networks (DCGAN) in Patients with Congenital Syndrome by Zika Virus

Érika G. Assis, Mark A. J. Song, Luis Enrique Zárate, Cristiane Neri Nobre. Data Balancing using Deep Convolutional Generative Adversarial Networks (DCGAN) in Patients with Congenital Syndrome by Zika Virus. In Nathalie Bier, Ana L. N. Fred, Hugo Gamboa, editors, Proceedings of the 15th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2022, Volume 5: HEALTHINF, Online Streaming, February 9-11, 2022. pages 93-102, SCITEPRESS, 2022. [doi]

@inproceedings{AssisSZN22,
  title = {Data Balancing using Deep Convolutional Generative Adversarial Networks (DCGAN) in Patients with Congenital Syndrome by Zika Virus},
  author = {Érika G. Assis and Mark A. J. Song and Luis Enrique Zárate and Cristiane Neri Nobre},
  year = {2022},
  doi = {10.5220/0010842900003123},
  url = {https://doi.org/10.5220/0010842900003123},
  researchr = {https://researchr.org/publication/AssisSZN22},
  cites = {0},
  citedby = {0},
  pages = {93-102},
  booktitle = {Proceedings of the 15th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2022, Volume 5: HEALTHINF, Online Streaming, February 9-11, 2022},
  editor = {Nathalie Bier and Ana L. N. Fred and Hugo Gamboa},
  publisher = {SCITEPRESS},
  isbn = {978-989-758-552-4},
}