Computerized Tongue Coating Nature Diagnosis Using Convolutional Neural Network

被引:0
作者
Fu, Shengyu [1 ]
Zheng, Hong
Yang, Zijiang [2 ]
Yan, Bo [1 ]
Su, Hongyi [1 ]
Liu, Yiping [1 ]
机构
[1] Beijing Inst Technol, Key Lab Intelligent Informat Technol, Beijing 100081, Peoples R China
[2] York Univ, Sch Informat Technol, Toronto, ON, Canada
来源
2017 IEEE 2ND INTERNATIONAL CONFERENCE ON BIG DATA ANALYSIS (ICBDA) | 2017年
关键词
tongue coating nature; Convolutional Neural Network(CNN); Image classification; Deep Learning;
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
Tongue coating nature inspection is an essential part in the tongue diagnosis of Traditional Chinese Medicine (TCM). However, it has been depending on doctors' visual judgment. Although many researches have been done in this field, the issue remains challenging. The approaches are limited to image processing or shallow neural networks. In this paper, we propose to computerize tongue coating nature using deep neural networks. The method combines the characteristics of basic image processing and deep learning. A standard and balanced tongue image dataset is used to validate the proposed method.
引用
收藏
页码:730 / 734
页数:5
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