@article{PATENT,
      recid = {7408},
      title = {Image transformation with a hybrid autoencoder and  generative adversarial network machine learning  architecture},
      number = {PATENT},
      month = {Oct},
      year = {2020},
      abstract = {An encoder artificial neural network (ANN) may be  configured to receive an input image patch and produce a  feature vector therefrom. The encoder ANN may have been  trained with a first plurality of domain training images  such that an output image patch visually resembling the  input image patch can be generated from the feature vector.  A generator ANN may be configured to receive the feature  vector and produce a generated image patch from the first  feature vector. The generator ANN may have been trained  with feature vectors derived from a first plurality of  domain training images and a second plurality of generative  training images such that the generated image patch  visually resembles the input image patch but is constructed  of a newly-generated image elements visually resembling one  or more image patches from the second plurality of  generative training images.},
      url = {http://knowledge.uchicago.edu/record/7408},
}