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Handwritten Devanagari Character Recognition using Convolutional Neural Network

机译:卷积神经网络的手写体梵文字符识别

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In any pattern recognition task, feature extraction and classification stages handle the responsibility of recognizing the patterns accurately. Deep learning relives the task of feature extraction and extracts them automatically, thus reducing the programmer's burden. Deep learning is replacing other pattern recognition techniques recently. In applications like character recognition, which involves large amount of database and variability in the data, deep learning is the right choice to handle the challenges involved. In this paper, a system for handwritten Devanagari character recognition using Convolutional Neural Network is discussed. The recognition accuracy obtained is 91.23% for Devanagari characters and 100% for Devanagari numerals.
机译:在任何模式识别任务中,特征提取和分类阶段都承担着准确识别模式的责任。深度学习重提了特征提取的任务并自动提取它们,从而减轻了程序员的负担。深度学习最近正在取代其他模式识别技术。在涉及大量数据库和数据可变性的字符识别等应用程序中,深度学习是应对所涉及挑战的正确选择。本文讨论了一种基于卷积神经网络的手写梵文字符识别系统。梵文字符的识别精度为91.23%,梵文数字的识别精度为100%。

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