Recognition of Handwritten Devanagari Character using Convolutional Neural Network

被引:2
|
作者
Dokare, Indu [1 ]
Gadge, Siddhesh [1 ]
Kharde, Kedar [1 ]
Bhere, Siddhesh [1 ]
Jadhav, Rohit [1 ]
机构
[1] VESIT, Dept Comp Engn, Mumbai, Maharashtra, India
关键词
Convolutional Network Layer; Devanagari; CNN Architecture; Devanagari Handwritten Character Dataset;
D O I
10.1109/ICSPC51351.2021.9451716
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
The use of a Convolutional Neural Network to recognize Devanagari characters is explored in this paper. Any pattern recognition task's classification stages and feature extraction are responsible for accurately defining the patterns. Deep learning surmounts the part of highlight extraction and does so consequently, encouraging the weight on software engineers. Deep learning is slowly but steadily displacing other pattern recognition methods. Deep learning is the best option to tackle the complexities involved in applications like character recognition, which require vast quantities of data and uncertainty in the data. Devanagari consonants have a recognition accuracy of 98 %, vowels have a recognition accuracy of 97.56 %, and Devanagari numerals have a recognition accuracy of 99 %.
引用
收藏
页码:353 / 359
页数:7
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