Convolution Operation Method and Apparatus, Computer Device, and Computer-Readable Storage Medium
AssigneeHangzhou Hikvision Digital Technology Co., Ltd.
InventorYuan Zhang
Life of this patent
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Abstract
Embodiments of the present application provide a method, an apparatus, a computer device for convolution operation and a computer readable storage medium. The method includes: obtaining input data of a network layer in a convolutional neural work; extracting each time a plurality of data points from the input data according to a preset step size; mapping the plurality of data points extracted each time to the same position at different depth levels of three-dimensional data to obtain rearranged data; and performing convolution operation on the rearranged data with a convolution kernel of a preset size to obtain a convolution result. Through the present solution, the operation efficiency of the convolutional neural network can be improved.
Claims11
A method for convolution operation, comprising:
- obtaining input data of a network layer in a convolutional neural work;
- extracting each time a plurality of data points from the input data according to a preset step size;
- mapping the plurality of data points extracted each time to the same position at different depth levels of three-dimensional data to obtain rearranged data;
- and
- performing convolution operation on the rearranged data with a convolution kernel of a preset size to obtain a convolution result.
An apparatus for convolution operation, comprising:
- an obtaining module, configure for obtaining input data of a network layer in a convolutional neural work;
- an extraction module, configured for extracting each time a plurality of data points from the input data according to a preset step size;
- a mapping module, configured for mapping the plurality of data points extracted each time to the same position at different depth levels of three-dimensional data to obtain rearranged data;
- and
- an operation module, configured for performing convolution operation on the rearranged data with a convolution kernel of a preset size to obtain a convolution result.
(canceled)
Dependencies are inferred from the claim text.