Periodontal Disease Detection Using Convolutional Neural Networks

被引：0
|
作者：
Joo, Jaehan [1 ]
Jeong, Sinjin [1 ]
Jin, Heetae [1 ]
Lee, Uhyeon [1 ]
Yoon, Ji Young [2 ]
Kim, Suk Chan [1 ]
机构：
[1] Pusan Natl Univ, Dept Elect & Comp Engn, Busan, South Korea
[2] Pusan Natl Univ, Dept Anesthesia & Pain Med, Busan, South Korea
来源：
2019 1ST INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE IN INFORMATION AND COMMUNICATION (ICAIIC 2019) | 2019年
基金：
新加坡国家研究基金会;
关键词：
Convolutional neural network; periodontal disease; periodontitis;
D O I：
10.1109/icaiic.2019.8669021
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper, we propose a classification method of periodontal disease based on CNN. The data to used were the actual periodontal images and non-periodontal images. Data processing techniques such as resize, crop and zero-centralizing are used to improve data learning efficiency. The CNN Structure proposed in this paper has 224 x 224 x 3 size image as input data and 4 outputs according to periodontal state. We also use momentum optimization technique for neural network optimization.
引用
收藏
页码：360 / 362
页数：3
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