The Handwritten Chinese Character Recognition use Convolutional neural networks with the GoogLenet

被引:0
|
作者
Chen, Jiahao [1 ]
Bi, Bing [1 ]
Yang, Kang [1 ]
Tan, Jun [1 ]
机构
[1] Sun Yat Sen Univ, Sch Math, Guangzhou, Peoples R China
基金
美国国家科学基金会;
关键词
CNN; GoogLenet; Handwritten recognition; Chinese character;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
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 with several necessary adjustments and also state-of-the-art improvement methods for this end-to-end approach. By the experiment 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 percent for the final version, which is encouraging for us to the further research and improvement.
引用
收藏
页码:2 / 7
页数:6
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