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All Journal IAES International Journal of Artificial Intelligence (IJ-AI)
Nguyen Thanh Nhan
Ho Chi Minh City University of Technology
Computer Science & IT Engineering

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Vietnamese handwritten character recognition using convolutional neural network Truong Quang Vinh; Le Hoai Duy; Nguyen Thanh Nhan
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 9, No 2: June 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (545.744 KB) | DOI: 10.11591/ijai.v9.i2.pp276-281

Abstract

Handwriting recognition is one of the core applications of computer vision for real-word problems and it has been gaining more interest because of the progression in this field. This paper presents an efficient model for Vietnamese handwriting character recognition by Convolutional Neural Networks (CNNs) – a kind of deep neural network model can achieve high performance on hard recognition tasks. The proposed architecture of the CNN network for Vietnamese handwriting character recognition consists of five hidden layers in which the first 3 layers are convolutional layers and the last 2 layers are fully-connected layers. Overfitting problem is also minimized by using dropout techniques with the reasonable drop rate. The experimental results show that our model achieves approximately 97% accuracy.
Co-Authors Le Hoai Duy Truong Quang Vinh