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Research Article 


A Machine Intelligence Based Model for the Classification of Odia Printed and Handwritten Images

Anupama Sahu, Sarojananda Mishra, Kalyan Kumar Jena.

Abstract
Language plays an important role for the communication among all of us. It is very much essential to detect the printed and handwritten language from several images to extract crucial information from it. In this paper, a machine intelligence (MI) based model is proposed for the classification of Odia printed and handwritten language (OPHL) from the analysis of several Odia language images. The proposed approach is mainly focused on the machine learning (ML) based hybridization mechanism. This mechanism focuses on the combination of the ML based methods such as Logistic Regression (LR) and Neural Network (NN) for the classification of printed and handwritten Odia images. The proposed method is compared with the ML based methods such as Support Vector Machine (SVM), Decision Tree (DT), K-Nearest Neighbour (KNN), AdaBoost (ADB) and Random Forest (RF) methods in terms of Classification Accuracy (CA) performance metric. The proposed method is able to classify the Odia printed and handwritten images in a better way as compared to other methods. The simulation of this work is carried out using Orange 3.26.0.

Key words: MI, ML, OPHL, SVM, DT, KNN, ADB, RF, LR, NN, CA


 
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How to Cite this Article
Pubmed Style

Anupama Sahu, Sarojananda Mishra, Kalyan Kumar Jena. A Machine Intelligence Based Model for the Classification of Odia Printed and Handwritten Images. EEO. 2021; 20(5): 3733-3744. doi:10.17051/ilkonline.2021.05.410


Web Style

Anupama Sahu, Sarojananda Mishra, Kalyan Kumar Jena. A Machine Intelligence Based Model for the Classification of Odia Printed and Handwritten Images. http://ilkogretim-online.org//?mno=68074 [Access: April 09, 2021]. doi:10.17051/ilkonline.2021.05.410


AMA (American Medical Association) Style

Anupama Sahu, Sarojananda Mishra, Kalyan Kumar Jena. A Machine Intelligence Based Model for the Classification of Odia Printed and Handwritten Images. EEO. 2021; 20(5): 3733-3744. doi:10.17051/ilkonline.2021.05.410



Vancouver/ICMJE Style

Anupama Sahu, Sarojananda Mishra, Kalyan Kumar Jena. A Machine Intelligence Based Model for the Classification of Odia Printed and Handwritten Images. EEO. (2021), [cited April 09, 2021]; 20(5): 3733-3744. doi:10.17051/ilkonline.2021.05.410



Harvard Style

Anupama Sahu, Sarojananda Mishra, Kalyan Kumar Jena (2021) A Machine Intelligence Based Model for the Classification of Odia Printed and Handwritten Images. EEO, 20 (5), 3733-3744. doi:10.17051/ilkonline.2021.05.410



Turabian Style

Anupama Sahu, Sarojananda Mishra, Kalyan Kumar Jena. 2021. A Machine Intelligence Based Model for the Classification of Odia Printed and Handwritten Images. Elementary Education Online, 20 (5), 3733-3744. doi:10.17051/ilkonline.2021.05.410



Chicago Style

Anupama Sahu, Sarojananda Mishra, Kalyan Kumar Jena. "A Machine Intelligence Based Model for the Classification of Odia Printed and Handwritten Images." Elementary Education Online 20 (2021), 3733-3744. doi:10.17051/ilkonline.2021.05.410



MLA (The Modern Language Association) Style

Anupama Sahu, Sarojananda Mishra, Kalyan Kumar Jena. "A Machine Intelligence Based Model for the Classification of Odia Printed and Handwritten Images." Elementary Education Online 20.5 (2021), 3733-3744. Print. doi:10.17051/ilkonline.2021.05.410



APA (American Psychological Association) Style

Anupama Sahu, Sarojananda Mishra, Kalyan Kumar Jena (2021) A Machine Intelligence Based Model for the Classification of Odia Printed and Handwritten Images. Elementary Education Online, 20 (5), 3733-3744. doi:10.17051/ilkonline.2021.05.410








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