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.

引用

页数：6

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