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US 11,687,775 B2Granted
Neural network data processing apparatus and method
AssigneeHuawei Technologies Co., Ltd.
InventorJacek Konieczny
Life of this patent
Estimating the term…
Abstract
Embodiments of the invention relates to a data processing apparatus comprising a processor configured to provide a neural network, wherein the neural network comprises a neural network layer being configured to generate from an array of input data values an array of output data values based on a plurality of position dependent kernels and a plurality of input data values of the array of input data values. Moreover, embodiments of the invention relates to a corresponding data processing method.
Claims21
A data processing apparatus comprising:
- a processor configured to:
- provide a neural network, wherein the neural network comprises a neural network layer configured to generate from an array of input data values and an array of output data values based on a plurality of position dependent kernels and a plurality of input data values of the array of input data values, wherein the neural network comprises an additional neural network layer configured to generate the plurality of position dependent kernels based on an original array of original input data values of the neural network, wherein the original array of original input data values of the neural network comprises the array of input data values or another array of input data values associated to the array of input data values, wherein the array of input data values and the array of output data values are two-dimensional arrays and wherein the neural network layer includes an upscaling network layer configured to generate the array of output data values on the basis of the following equations:
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- wherein x, y, x′, y′, i, j denote array indices, out(x, y) denotes the array of output data values, in(x′, y′) denotes the array of input data values, r denotes a size of each kernel of the plurality of position dependent kernels wL(x′, y′, i, j) and WL′(x, y) denotes a normalization factor.
163 more elements
A data processing method comprising:
- generating by a neural network layer of a neural network from an array of input data values and an array of output data values based on a plurality of position dependent kernels and a plurality of different input data values of the array of input data values, wherein the neural network comprises an additional neural network layer configured to generate the plurality of position dependent kernels based on an original array of original input data values of the neural network, wherein the original array of original input data values of the neural network comprises the array of input data values or another array of input data values associated to the array of input data values, wherein the array of input data values and the array of output data values are two-dimensional arrays and wherein the neural network layer includes an upscaling network layer configured to generate the array of output data values on the basis of the following equations:
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142 more elements
A non-transitory computer-readable medium comprising program code stored therein, which when executed by a processor, causes the processor to perform operations comprising:
- generating by a neural network layer of a neural network from an array of input data values and an array of output data values based on a plurality of position dependent kernels and a plurality of different input data values of the array of input data values, wherein the neural network comprises an additional neural network layer configured to generate the plurality of position dependent kernels based on an original array of original input data values of the neural network, wherein the original array of original input data values of the neural network comprises the array of input data values or another array of input data values associated to the array of input data values, wherein the array of input data values and the array of output data values are two-dimensional arrays and wherein the neural network layer includes an upscaling network layer configured to generate the array of output data values on the basis of the following equations:
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- wherein x, y, x′, y′, i, j denote array indices, out (x, y) denotes the array of output data values, in(x′, y′) denotes the array of input data values, r denotes a size of each kernel of the plurality of position dependent kernels wL(x′, y′, i, j) and WL′(x, y) denotes a normalization factor.
142 more elements
Dependencies are inferred from the claim text.