Convolutional Neural Networks Applied to Handwritten Mathematical Symbols Classification

被引：0

作者：

Ramadhan, Irwansyah ^{[1
]}

Purnama, Bedy ^{[1
]}

Al Faraby, Said ^{[1
]}

机构：

[1] Telkom Univ, Sch Comp, Bandung, Indonesia

来源：

2016 4TH INTERNATIONAL CONFERENCE ON INFORMATION AND COMMUNICATION TECHNOLOGY (ICOICT) | 2016年

关键词：

convolutional neural networks; pattern recognition; handwritten mathematical symbols recognition;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Convolutional Neural Networks have achieved great performance in computer vision and pattern recognition applications. In this work, we propose the use of Convolutional Neural Networks in order to improve the handwritten mathematical symbol classification rate. We trained a Convolutional Neural Networks to classifying mathematical symbols into a proper class using Competition on Recognition of Online Handwritten Mathematical Expressions (CROHME) 2014 dataset. The results show that Convolutional Neural Networks outperforms the previous works in terms of accuracy.

引用

页数：4

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