实现一种混合深度学习方法实现经典手写字母数字莫迪识别

M. Ekbote, Aishwarya Jadhav, D. Ambawade
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引用次数: 0

摘要

莫迪是梵文的同义词,是一种来自17世纪的古老文字,被马拉地帝国用作文化和权力的象征,以传播马拉地语。由于其使用率下降,缺乏高质量的脚本数据库和缺乏良好的文献,对莫迪脚本的识别和翻译是很有必要的。本文研究了一种基于卷积神经网络(CNN)结构的MODI字符和数字识别的新方法。通过使用传统的机器学习分类器进行分类,然后通过Random Forest和XGBoost的对比分析,本研究对字符的识别准确率达到92%,对数字的识别准确率达到93.3%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Implementing a Hybrid Deep Learning Approach to Achieve Classic Handwritten Alphanumeric MODI Recognition
MODI, synonymous with the Devanagari script, is an ancient script from the 17th century used by the Maratha empire as a symbol of culture and power to propagate Marathi. Due to a decline in its usage, absence of quality script database and an unavailability of good literature, identification and translation of MODI script is demanding. The present work deals with a novel study on the recognition of MODI characters and numerals by using Convolutional Neural Network (CNN) architecture. By using a traditional machine learning classifier, classification is performed, and then through a comparative analysis of Random Forest and XGBoost, the study achieves recognition accuracy of 92% for characters and 93.3% for numerals.
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