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Processing method by convolutional neural network, learning method of convolutional neural network, and processing device including convolutional neural network

机译:卷积神经网络的处理方法,卷积神经网络的学习方法以及包括卷积神经网络的处理装置

摘要

In a processing method using a convolutional neural network, the neural network includes a convolution calculation unit that performs a convolution calculation by using a matrix vector product and a pooling calculation unit that performs a maximum value sampling calculation. A threshold value is set related to the matrix data for the convolution calculation, the matrix data is divided into a first and second halves based on the threshold value. The convolution calculation unit divides a first half convolution calculation by using the first half of the matrix data and a second half convolution calculation by using the second half of the matrix data into two and executes the calculations. The pooling calculation unit selects vector data to which the matrix vector product convolution calculation is to be performed in the second half convolution calculation, along with the maximum value sampling calculation.
机译:在使用卷积神经网络的处理方法中,该神经网络包括:卷积计算单元,其通过使用矩阵矢量积来执行卷积计算;以及池化计算单元,其进行最大值采样计算。设置与矩阵数据有关的阈值以进行卷积计算,基于该阈值将矩阵数据分为第一半和第二半。卷积计算单元将通过使用矩阵数据的前半部分的前半部分卷积计算和通过使用矩阵数据的后半部分的后半部分卷积计算分为两部分并执行计算。合并计算单元选择在后半卷积计算中要对其执行矩阵矢量积卷积计算的矢量数据,以及最大值采样计算。

著录项

  • 公开/公告号JP6738296B2

    专利类型

  • 公开/公告日2020-08-12

    原文格式PDF

  • 申请/专利权人 株式会社日立製作所;

    申请/专利号JP20170056780

  • 发明设计人 本谷 徹;小野 豪一;豊田 英弘;

    申请日2017-03-23

  • 分类号G06N3/04;G06F17/10;G06F17/16;

  • 国家 JP

  • 入库时间 2022-08-21 11:35:34

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