Teeth Classification Based on Extreme Learning Machine

被引：0

作者：

Lu, Siyuan ^{[1
]}

Yang, Jingyuan ^{[2
]}

Wang, William ^{[3
]}

Li, Zhi ^{[4
]}

Lu, Zhihai ^{[1
]}

机构：

[1] Nanjing Normal Univ, Sch Math Sci, Nanjing 210023, Jiangsu, Peoples R China

[2] Xian Univ Technol, Fac Comp Sci & Engn, Xian 710048, Shaanxi, Peoples R China

[3] Waynesburg Univ, Waynesburg, PA 15370 USA

[4] Jinling Hosp, Dept Stomatol, Nanjing 210002, Jiangsu, Peoples R China

来源：

PROCEEDINGS OF THE 2018 SECOND WORLD CONFERENCE ON SMART TRENDS IN SYSTEMS, SECURITY AND SUSTAINABILITY (WORLDS4) | 2018年

关键词：

Teeth Classification; principle component analysis; extreme learning machine; PATHOLOGICAL BRAIN DETECTION; NEURAL-NETWORK; IMAGE CLASSIFICATION; OPTIMIZATION;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Teeth are important organs in vertebrates. The accurate classification of teeth is beneficial for dentists to diagnose. In this manuscript, we put forward a novel teeth classification algorithm combined principle component analysis and extreme learning machine. Principle component analysis was used to extract features from the teeth images and extreme learning machine served as the classifier. Experimental results suggested that our method is effective in identification of four categories of teeth.

引用

页码：198 / 202

页数：5

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