Research on Handwriting Recognition Algorithm Based on Convolution Neural Network

DOI

10.2991/ncce-18.2018.60How to use a DOI?

Keywords

deep learning, convolutional neural network, Handwritten character

Abstract

Since Geoffrey Hinton first proposed the concept of deep learning in 2006, which in Reducing the dimensionality of data with neural networks, deep learning has been the continuous concern of the researchers. Deep learning uses a multi-layer neural network to simulate the multi-layer abstract learning process of the human brain. The network structure design and feature extraction are the key problems in the application of data mining and pattern recognition. The accuracy of deep learning for handwritten digital recognition has always been an important criterion for measuring a deep learning algorithm or network structure. In this paper, a handwritten character recognition algorithm based on convolution neural network is studied and compared with other recognition algorithms, and the error rate in their recognition is compared

Copyright

© 2018, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Download article (PDF)

TY  - CONF
AU  - Pengfei Hu
AU  - Hao Tang
PY  - 2018/05
DA  - 2018/05
TI  - Research on Handwriting Recognition Algorithm Based on Convolution Neural Network
BT  - Proceedings of the 2018 International Conference on Network, Communication, Computer Engineering (NCCE 2018)
PB  - Atlantis Press
SP  - 376
EP  - 379
SN  - 1951-6851
UR  - https://doi.org/10.2991/ncce-18.2018.60
DO  - 10.2991/ncce-18.2018.60
ID  - Hu2018/05
ER  -