Practical Convolutional Neural Networks

CycleGAN 

CycleGAN is also an image-to-image translator but without input/output pairs. For example, to generate photos from paintings, convert a horse image into a zebra image:

In a discriminator network, use of dropout is important. Otherwise, it may produce a poor result.

The generator network takes random noise as input and produces a realistic image as output. Running a generator network for different kinds of random noise produces different types of realistic images. The second network, which is known as the discriminator network, is very similar to a regular neural net classifier. This network is trained on real images, although training ...