Hand-written Numeral Recognition Based on Probabilistic Neural Network

DOI

10.2991/iccmcee-15.2015.121How to use a DOI?

Keywords

probability neural network; hand-written numeral recognition; model recognition

Abstract

This paper analyzes favorable properties and realization principles of probabilistic neural network and elaborates the original image pre-processing and normalization processing of hand-written numeral, proper vector extraction, network model building, and other key techniques. Finally, this paper checks the model of hand-written numeral recognition based on probabilistic neural network, the results of which show that this model has high recognition accuracy and strong stability.

Copyright

© 2015, 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/).

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TY  - CONF
AU  - Jun Zheng
PY  - 2015/11
DA  - 2015/11
TI  - Hand-written Numeral Recognition Based on Probabilistic Neural Network
BT  - Proceedings of the 2015 4th International Conference on Computer, Mechatronics, Control and Electronic Engineering
PB  - Atlantis Press
SP  - 672
EP  - 676
SN  - 2352-5401
UR  - https://doi.org/10.2991/iccmcee-15.2015.121
DO  - 10.2991/iccmcee-15.2015.121
ID  - Zheng2015/11
ER  -