文章基本信息

标题：Deep Learning Based Models for Offline Gurmukhi Handwritten Character and Numeral Recognition
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作者：Manoj Kumar Mahto ; Karamjit Bhatia ; Rajendra Kumar Sharma 等
期刊名称：ELCVIA: electronic letters on computer vision and image analysis
印刷版ISSN：1577-5097
出版年度：2022
卷号：20
期号：2
DOI：10.5565/rev/elcvia.1282
语种：English
出版社：Centre de Visió per Computador
摘要：Over the last few years, several researchers have worked on handwritten character recognition and have proposed various techniques to improve the performance of Indic and non-Indic scripts recognition. Here, a Deep Convolutional Neural Network has been proposed that learns deep features for offline Gurmukhi handwritten character and numeral recognition (HCNR). The proposed network works efficiently for training as well as testing and exhibits a good recognition performance. Two primary datasets comprising of offline handwritten Gurmukhi characters and Gurmukhi numerals have been employed in the present work. The testing accuracies achieved using the proposed network is 98.5% for characters and 98.6% for numerals.