US Patent 9858525 System for training networks for semantic segmentation

Disclosed herein are technologies directed to training a neural network to perform semantic segmentation. A system receives a training image, and using the training image, candidate masks are generated. The candidate masks are ranked and a set of the ranked candidate masks are selected for further processing. One of the set of the ranked candidate masks is selected to train the neural network. The one of the set of the set of the ranked candidate masks is also used as an input to train the neural network in a further training evolution. In some examples, the one of the set of the ranked candidate masks is selected randomly to reduce the likelihood of ending up in poor local optima that result in poor training inputs.