Anomaly Detection of Arm X-Ray Based on Deep Learning

被引：0
|
作者：
Wang, Jingchen [1 ]
机构：
[1] Phillips Exeter Acad, 20 Main St, Exeter, NH 03833 USA
来源：
2019 5TH INTERNATIONAL CONFERENCE ON ENVIRONMENTAL SCIENCE AND MATERIAL APPLICATION | 2020年 / 440卷
关键词：
D O I：
10.1088/1755-1315/440/4/042056
中图分类号：
X [环境科学、安全科学];
学科分类号：
08 ; 0830 ;
摘要：
The goal of this paper is to determine whether the arm has a fracture by detecting the X-ray of the human arm. This paper used the Keras deep learning framework and use the NASNetMobile model for training. The data set is MURA-v1.1, and the test accuracy on the verification set is about 70%. After downloading X-ray photographs of fractured arms, this paper performed an anomaly detection of the single image to test the accuracy of the model.
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页数：6
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