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

页码：360 / 362

页数：3

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