Pooling processing method and system applied to convolutional neural network

Abstract

This application discloses a pooling processing method, applied to a pooling processing system of a convolutional neural network. The method includes receiving a feature map comprising a width dimension and a height dimension; establishing a data region comprising k+m columns and n rows, k, m, and n being integers; transferring data blocks each of size k in width and size n in height from the feature map in a width-height sequential scanning order into columns m+1 to k+m and rows 1 to n of the data region in pooling cycles; and in each pooling cycle corresponding to a data block transferred from the feature map to the data region: retaining columns k+1 to k+m of the data region of a previous pooling cycle to columns 1 to m of the data region; performing a first level pooling within each column of the data region to obtain k+m first level pooling values; and performing P second level pooling values by pooling P sets of first level pooling values selected according to a position of the data block relative to a width boundary in the feature map, P being an integer.