No confident code implementation found for this paper. 3 possible matches can be shown below.
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.
No confident code match yet
We couldn't find an author-owned or strongly-evidenced community implementation for this paper. 3 weaker matches are hidden by default — verify before relying on them.
No code implementations found yet.
Know of an implementation? Let us know in the comments below!
Fine-Tuning Cycle-GAN for Domain Adaptation of MRI Images
Structure Preserving Cycle-GAN for Unsupervised Medical Image Domain Adaptation
A Strictly Bounded Deep Network for Unpaired Cyclic Translation of Medical Images
A Parameterized Generative Adversarial Network Using Cyclic Projection for Explainable Medical Image Classification
CycleGAN with Better Cycles
CyCADA: Cycle-Consistent Adversarial Domain Adaptation
@article{zhao2026example,
title = {An Example for Domain Adaptation Using CycleGAN},
author = {Yanhua Zhao},
year = {2026},
eprint = {2601.08776},
archivePrefix = {arXiv},
url = {http://arxiv.org/abs/2601.08776v3}
}Shows whether official code is linked for this paper.
[](https://codeofpaper.com/paper/2601.08776)