Training convolutional variational autoencoders
Iam trying to train a convolutional variational autoencoder (CVAE) on computed tomography (CT) IMAGES (176X224 px) . The training data is normalized between 0 and 1 and Iam using approximately the same model structure as in keras autoencoder tutorial.
I only changed the depth and the size of the latent space to 128.
For the loss function I use Mse and KL, with a weight annealing for the KL part.
When I train the network it seems like it is learning something, but if I try to reconstruct images after training, the output images are just noisy.
I have no clue what it is Iam doing wrong.
Any advice would be really great.