Fig. 4

Representation of a generative adversarial network (GAN). This GAN aims at filling holes in an image (‘inpainting’, i.e., imputation). The generator network simulates a new image out of the input picture of the cow, which does not have front legs. The discriminator is trained with images that are true or fake and learns how a real cow looks like. The generator discriminates whether the generated image is true or fake, the result is passed on to the generator so that it can improve the quality of the output image. Each of the rectangles in the generator and the discriminator represent a group of neuron layers as in Fig. 3, the shape is approximately proportional to its dimension. The figure of the cow is from www.dreamstime.com