Open AccessJournal Article
Handwritten Devanagari Character Recognition Model Using Neural Network
TLDR
A recognition model is described for recognizing handwritten Devanagari characters and achieves the accuracy rate of recognition which range from 75% to 80%.Abstract:
In this paper, a recognition model is described for recognizing handwritten Devanagari characters. The scanned image database of handwritten Devanagari character form several different writers was used to train and test to this classifier model. This model first preprocess (normalization, binarization, crop) then extracts the feature set. Based on the extracted feature database it classifies the characters. This model achieves the accuracy rate of recognition which range from 75% to 80%.read more
Citations
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Proceedings ArticleDOI
A Deep Learning Approach for Optical Character Recognition of Handwritten Devanagari Script
Brijeshwar Dessai,Amit Patil +1 more
TL;DR: Development of Convolutional Neural Network (CNN) based Optical Character Recognition system (OCR) for Handwritten Devanagari Script which is observed to recognize the characters accurately.
Journal ArticleDOI
Performance Evaluation of Feed-Forward Neural Network Models for Handwritten Hindi Characters with Different Feature Extraction Methods
Journal ArticleDOI
A Review of Different Approaches Used for Devanagari Character Recognition
Mayank Sahai,Neha Sahu +1 more
TL;DR: Some of the popular research performed in recognizing Devanagari script are enlightened and various advantage and scope of using different methodology including Bounding Box technique, Ostu’s algorithm, neural networks and many more are summarized.
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