%0 Journal Article %1 Jabbar_2022 %A Jabbar, Abdul %A Li, Xi %A Omar, Bourahla %D 2022 %I Association for Computing Machinery (ACM) %J ACM Computing Surveys %K 2022 GAN network survey %N 8 %P 1--49 %R 10.1145/3463475 %T A Survey on Generative Adversarial Networks: Variants, Applications, and Training %U https://doi.org/10.1145%2F3463475 %V 54

@article{Jabbar_2022, added-at = {2021-10-06T12:15:50.000+0200}, author = {Jabbar, Abdul and Li, Xi and Omar, Bourahla}, biburl = {https://www.bibsonomy.org/bibtex/27cb12c53377176c2b93001dd6e6ee8db/analyst}, description = {A Survey on Generative Adversarial Networks: Variants, Applications, and Training | ACM Computing Surveys}, doi = {10.1145/3463475}, interhash = {0d3a23af6aa50851107bdc97926f1555}, intrahash = {7cb12c53377176c2b93001dd6e6ee8db}, journal = {{ACM} Computing Surveys}, keywords = {2022 GAN network survey}, month = nov, number = 8, pages = {1--49}, publisher = {Association for Computing Machinery ({ACM})}, timestamp = {2021-10-06T12:15:50.000+0200}, title = {A Survey on Generative Adversarial Networks: Variants, Applications, and Training}, url = {https://doi.org/10.1145%2F3463475}, volume = 54, year = 2022 }