Modified Convolutional Network for the Identification of Covid-19 with a Mobile System

被引：0
|
作者：
Lin Jzau-Sheng [1 ]
Fang Shen An [1 ]
Li Cheng Ze [1 ]
机构：
[1] Natl Chin Yi Univ Technol, Dept Comp Sci Informat Engn, Taichung, Taiwan
来源：
22ND IEEE/ACIS INTERNATIONAL CONFERENCE ON SOFTWARE ENGINEERING, ARTIFICIAL INTELLIGENCE, NETWORKING AND PARALLEL/DISTRIBUTED COMPUTING (SNPD 2021-FALL) | 2021年
关键词：
COVID-19; Deep learning; MobileNet;
D O I：
10.1109/SNPD51163.2021.9705004
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
In this paper, we modified a low-cost and rapid method to detect chest X-rays based on MobileNet. Because MobileNet is a lightweight neural network, we modified and optimized backpropagation learning to train the model. In the subsequent COVID-19, pneumonia, and normal tests, the recognition accuracy reached 99.14%, which greatly improved the performance of the model.Our scheme can produce an effective model suitable for low-performance mobile devices.
引用
收藏
页码：187 / 190
页数：4
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