Cycle-Consistent Adversarial Network (CycleGAN) is very promising in domain adaptation. In this report, an example in medical domain will be explained. We present struecture of a CycleGAN model for unpaired image-to-image translation from microscopy to pseudo H\&E stained histopathology images.

翻译：循环一致性对抗网络（CycleGAN）在领域自适应任务中展现出巨大潜力。本报告将以医学领域为例进行阐释，提出一种用于从显微图像到伪H&E染色组织病理学图像的非配对图像转换的CycleGAN模型结构。