A Comparative Study of Handwritten Mathematical Symbols Recognition

2016 13th International Conference on Computer Graphics, Imaging and Visualization (CGiV) Pub Date : 2016-03-01 DOI:10.1109/CGIV.2016.92

Yassine Chajri, Abdelkrim Maarir, B. Bouikhalene

引用次数: 7

Abstract

In this paper we are going to apply four descriptors (GIST, PHOG, SURF and Centrist) and two classifiers (Artificial Neural Network (ANN) and Support Vector Machines (SVM)) for handwritten mathematical symbols recognition to achieve a comparative study based on the recognition rate.

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手写体数学符号识别的比较研究

本文将四种描述符(GIST、PHOG、SURF和Centrist)和两种分类器(人工神经网络(ANN)和支持向量机(SVM))应用于手写数学符号识别，基于识别率进行对比研究。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

2016 13th International Conference on Computer Graphics, Imaging and Visualization (CGiV)

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