Title:
畳み込みニューラルネットワーク
Document Type and Number:
Japanese Patent JP6724863
Kind Code:
B2
Abstract:
A convolutional neural network includes: convolution layers and a merging layer. At least one convolution layer includes a crossbar circuit having input bars, output bars and weight assignment elements that assign weights to input signals. The crossbar circuit performs a convolution operation in an analog region with respect to input data including the input signal by adding the input signals at each output bar. The input data includes feature maps. The crossbar circuit includes a first crossbar circuit for performing the convolution operation with respect to a part of the feature maps and a second crossbar circuit for performing the convolution operation with respect to another part of feature maps. The merging layer merges convolution operation results of the first and second crossbar circuits.
Inventors:
Kataheva Irina
Application Number:
JP2017105742A
Publication Date:
July 15, 2020
Filing Date:
May 29, 2017
Export Citation:
Assignee:
株式会社デンソー
International Classes:
G06N3/063; G06G7/60
Foreign References:
| US9646243 |
Other References:
YAKOPCIC, Chris et al.,"Memristor Crossbar Deep Network Implementation Based on a Convolutional Neural Network",2016 International Joint Conference on Neural Networks (IJCNN) [online],米国,IEEE,2016年,pp.963-970,[検索日 2018.06.11],URL,https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7727302
Attorney, Agent or Firm:
Kazuyuki Yahagi
Taihei Nonobe
Takanori Kubo
Taihei Nonobe
Takanori Kubo