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All Journal International Journal of Electrical and Computer Engineering
Bipin Nair Balakrishnan Jayakumari
Amrita Vishwa Vidyapeetham
Computer Science & IT Electrical & Electronics Engineering

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Classification of heterogeneous Malayalam documents based on structural features using deep learning models Bipin Nair Balakrishnan Jayakumari; Amel Thomas Kavana
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 1: February 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i1.pp894-901

Abstract

The proposed work gives a comparative study on performance of various pretrained deep learning models for classifying Malayalam documents such as agreement documents, notebook images, and palm leaves. The documents are classified based on their visual and structural features. The dataset was manually collected from different sources. The method of research proceeds with preprocessing, feature extraction, and classification. The proposed work deals with three fine-tuned deep learning models such as visual geometry group-16 (VGG-16), convolutional neural network (CNN) and AlexNet. The models attained high accuracies of 99.7%, 96%, and 95%, respectively. Among the three models, the fine-tuned VGG-16 model was found to perform better attaining a very high accuracy on the dataset. As a future work, methods to classify the documents based on content as well as spectral features can be developed.
Co-Authors Amel Thomas Kavana