Article Per Year (5 Year)
p-Index From 2021 - 2026
0.23
P-Index
This Author published in this journals
All Journal Bulletin of Electrical Engineering and Informatics
Satori, Khalid
Unknown Affiliation
Electrical & Electronics Engineering

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
Improving Arabic handwritten text recognition through transfer learning with convolutional neural network-based models Lamtougui, Hicham; El Moubtahij, Hicham; Fouadi, Hassan; Satori, Khalid
Bulletin of Electrical Engineering and Informatics Vol 13, No 6: December 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v13i6.8178

Abstract

Arabic handwritten text recognition is a complex and challenging research domain. This study proposes an offline Arabic handwritten word recognition system based on transfer learning. The system exploits four pre-trained convolutional neural network (CNN) architectures, namely VGG16, ResNet50, AlexNet, and InceptionV3. In addition, a specialized image recognition model derived from the ImageNet dataset is incorporated. A combination strategy is designed to combine transfer learning with specific fine-tuning techniques, aiming to improve recognition accuracy. The study is conducted on the IFN/ENIT dataset, which includes images of Tunisian City and village names. The results show that the proposed system achieves a recognition accuracy of 94.73%, which is significantly higher than the accuracy rates achieved by previous approaches. These results suggest that the proposed system is a promising approach for Arabic handwritten text recognition.
Co-Authors EL Moubtahij, Hicham Fouadi, Hassan Lamtougui, Hicham