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首页> 外文期刊>International Journal of Pattern Recognition and Artificial Intelligence >The Handwritten Chinese Character Recognition Uses Convolutional Neural Networks with the GoogLeNet
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The Handwritten Chinese Character Recognition Uses Convolutional Neural Networks with the GoogLeNet

机译:手写汉字识别通过GoogLeNet使用卷积神经网络

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摘要

With the outstanding performance in 2014 at the ImageNet Large-Scale Visual Recognition Challenge 2014 (ILSVRC14), an effective convolutional neural network (CNN) model named GoogLeNet has drawn the attention of the mainstream machine learning field. In this paper we plan to take an insight into the application of the GoogLeNet in the Handwritten Chinese Character Recognition (HCCR) on the database HCL2000 and CASIA-HWDB with several necessary adjustments and also state-of-the-art improvement methods for this end-to-end approach. Through the experiments we have found that the application of the GoogLeNet for the Handwritten Chinese Character Recognition (HCCR) results into significant high accuracy, to be specific more than 99% for the final version, which is encouraging for us to further research.
机译:在2014年ImageNet大规模视觉识别挑战赛(ILSVRC14)上,2014年表现出色,一个名为GoogLeNet的有效卷积神经网络(CNN)模型引起了主流机器学习领域的关注。在本文中,我们计划深入了解GoogLeNet在HCL2000和CASIA-HWDB数据库上的手写汉字识别(HCCR)中的应用,并为此进行了一些必要的调整以及最先进的改进方法端到端的方法。通过实验,我们发现GoogLeNet在手写汉字识别(HCCR)中的应用导致了很高的准确性,最终版本的准确率超过了99%,这为我们的进一步研究提供了鼓励。

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