Overview of our study. (a) Training process. This image is reproduced from Jeong et al. (2022). The generator (G) takes input images (AIA 171 and AIA 304 Å) and translates them into new images. The red box at the boundary of the images indicates the generator images. The discriminator (D) distinguishes between real pairs and fake pairs. The inspector (I) guides the generator by computing concordance CC values, ensuring the generated images are not only realistic but also scientifically accurate according to the data relationships. To utilize this model, we first trained five models for each channel (94, 131, 193, 211, and 335 Å) using only the AIA observed dataset. (b) Applying process. After we successfully trained the models, we applied the generative models to the FSI observed dataset. The dashed blue line shows the results when a deep learning model was applied to the FSI dataset. Finally, the observed FSI 174 Å with AI-generated sets could determine the DEMs.