Figure 4. Examples of deep learning methods. In the top row are two different images with different pixel problems. The blue and red marks show two moving objects. The bottom row shows the same images after they have been denoised, and the problems have also been removed without damaging the sources in the images.
As another example, the deep models can also be used as a content-based recommendation system capable of filtering images based on the desired content (see Teimoorinia et al., 2021). In Figure 5 (a Self Organizing Map), different sources of a set of astronomical images are modeled by a deep model. The model is capable of recognizing images with bad pixels (e.g., the sources similar to node (1, 12)), images with a bad focus problem (e.g., node (2, 1)) or images with satellite tracks (e.g., node (23, 1)).
