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Character Recognition using Machine Learning and Deep Learning - A Survey

机译:使用机器学习和深度学习进行字符识别的调查

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Digitization of machine printed or handwritten text documents have become very popular with the advancements in computing and technology. Humans have tried to automatized their work by replacing themselves with machines. The transformation from manual to automatization gave rise to several research areas and text recognition is one among them. Deep learning and machine learning techniques have been proved to be very suitable for optical character recognition. In this work, an up-to-date overview of four machine learning and deep learning architectures, viz., Support vector machine, Artificial neural network, Naive Bayes and Convolutional neural network have been discussed in detail.
机译:随着计算和技术的发展,机器打印或手写文本文档的数字化已变得非常流行。人们试图通过用机器代替自己来使他们的工作自动化。从手动到自动化的转变引起了几个研究领域,而文本识别就是其中之一。深度学习和机器学习技术已被证明非常适合光学字符识别。在这项工作中,详细讨论了四种机器学习和深度学习架构的最新概述,即支持向量机,人工神经网络,朴素贝叶斯和卷积神经网络。

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