End-To-End Retina Image Synthesis Based on CGAN Using Class Feature Loss and Improved Retinal Detail Loss

Nan Liang, Liming Yuan, Xianbin Wen, Haixia Xu 0003, Jingyi Wang. End-To-End Retina Image Synthesis Based on CGAN Using Class Feature Loss and Improved Retinal Detail Loss. IEEE Access, 10:83125-83137, 2022. [doi]

@article{LiangYWXW22,
  title = {End-To-End Retina Image Synthesis Based on CGAN Using Class Feature Loss and Improved Retinal Detail Loss},
  author = {Nan Liang and Liming Yuan and Xianbin Wen and Haixia Xu 0003 and Jingyi Wang},
  year = {2022},
  doi = {10.1109/ACCESS.2022.3196377},
  url = {https://doi.org/10.1109/ACCESS.2022.3196377},
  researchr = {https://researchr.org/publication/LiangYWXW22},
  cites = {0},
  citedby = {0},
  journal = {IEEE Access},
  volume = {10},
  pages = {83125-83137},
}