In the standard 2D-SIM set-up, we need 9 images to reconstruct a super-resolution image. We want to reduce the number of images (to have fast acquisition + to limit the photo-toxicity + to make longer experiment) while keeping almost the same quality. Hence, we need to train a neural network to learn the missing information from the data.