Patent ID: 9704068
Date: 2017-07-11
CPC Classifications: G06K,G06N,G06T

Claim:
1. A method performed by one or more computers, the method comprising: training a neural network on training data, wherein the training data includes a plurality of labeled aerial images, wherein the neural network is configured to select a random patch of an input aerial image, modify the random patch with asymmetric noise based on a translation parameter, and generate a respective score for each of a plurality of pixels of the random patch, wherein the translation parameter (i) accounts for potential translation errors for labels in the labeled aerial images, and (ii) parameterizes a translation distribution from which a value of a translation variable is sampled during the training, wherein the respective scores for each of the plurality of pixels represent a probability that the pixel belongs to an object class, and wherein training the neural network on the training data comprises: