Neural network trained with spatial errors
First Claim
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1. A method of using a computer to train a computer-based neural network with input image data, the neural network including a plurality of connection weights, the method comprising:
- using the neural network to rescale the input image data;
determining errors for the rescaled data; and
using neighborhoods of the errors to adjust the connection weights.
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Abstract
A neural network is trained with input data. The neural network is used to rescale the input data. Errors for the rescaled values are determined, and neighborhoods of the errors are used adjust connection weights of the neural network.
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Citations
37 Claims
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1. A method of using a computer to train a computer-based neural network with input image data, the neural network including a plurality of connection weights, the method comprising:
- using the neural network to rescale the input image data;
determining errors for the rescaled data; and
using neighborhoods of the errors to adjust the connection weights. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18)
- using the neural network to rescale the input image data;
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19. A method of using image input data and target data to train a neural network for image upscaling, the method comprising:
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using the neural network to generate predicted values from the input data; determining errors for the predicted values, the error for each predicted value a function of differences between predicted values in a spatial neighborhood and the corresponding values in the target data; and back-propagating the errors through the neural network.
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20. Apparatus for training a neural network on input data, the apparatus comprising:
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means for using the neural network to rescale the input data; means for determining errors for the rescaled data; and means for using neighborhoods of the errors to adjust the connection weights.
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21. Apparatus for training a neural network on input data to perform image rescaling, the neural network having a plurality of connection weights, the apparatus comprising a processor programmed to use the neural network to rescale the input data;
- determine errors for the rescaled data; and
use neighborhoods of the errors to adjust the connection weights of the neural network. - View Dependent Claims (22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 36)
- determine errors for the rescaled data; and
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34. Apparatus for rescaling a color image, the apparatus comprising:
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means for rescaling the input image by pixel replication; a neural network that has been trained to rescale a luminance channel of the color image, the neural network for producing a rescaled luminance image; and means for using the rescaled luminance image and the pixel-replicated image to generate a rescaled color image. - View Dependent Claims (35)
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37. An article for causing a processor to use input image data to adjust connection weights of a neural network so the neural network can perform image rescaling, the article comprising:
computer memory; and
data encoded in the computer memory, the data causing the processor to use the neural network to rescale the input image data;
determine errors for the rescaled data; and
use neighborhoods of the errors to adjust the connection weights of the neural network.
Specification