Recognition of Isolated Handwritten Arabic Characters

被引：4
|
作者：
Almansari, Osamah Abdulrahman [1 ]
Hashim, Nik Nur Wahidah Nik [1 ]
机构：
[1] Int Islamic Univ Malaysia, Dept Mechatron Engn, Kuala Lumpur, Malaysia
来源：
2019 7TH INTERNATIONAL CONFERENCE ON MECHATRONICS ENGINEERING (ICOM) | 2019年
关键词：
Handwriting Recognition; MLP; Arabic Database; CNN; character recognition;
D O I：
10.1109/icom47790.2019.8952035
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
The challenges that face the handwritten Arabic recognition are overwhelming such as different varieties of handwriting and few public databases available. Also, teaching the non-Arabic speaker at the young age is very difficult due to the unfamiliarity of the words and meanings. So, this project is focused on building a model of a deep learning architecture with convolutional neural network (CNN) and multilayer perceptron (MLP) neural network by using python programming language. This project analyzes the performance of a public database which is Arabic Handwritten Characters Dataset (AHCD). However, training this database with CNN model has achieved a test accuracy of 95.27% while training it with MLP model achieved 72.08%. Therefore, the CNN model is suitable to be used in the application device.
引用
收藏
页码：107 / 111
页数：5
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