1 research outputs found
Recognition of isolated handwritten Arabic characters
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