Learning to Label Aerial Images from Noisy Data

  title={Learning to Label Aerial Images from Noisy Data},
  author={Volodymyr Mnih and Geoffrey E. Hinton},
When training a system to label images, the amount of labeled training data tends to be a limiting factor. We consider the task of learning to label aerial images from existing maps. These provide abundant labels, but the labels are often incomplete and sometimes poorly registered. We propose two robust loss functions for dealing with these kinds of label noise and use the loss functions to train a deep neural network on two challenging aerial image datasets. The robust loss functions lead to… CONTINUE READING
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