A SVM-based approach for detecting tendon Injury

被引：0

作者：

Borzooei, Sahar ^{[1
]}

Tournier, Pierre-Henri ^{[2
]}

Dolean, Victorita ^{[1
]}

Migliaccio, Claire ^{[3
]}

机构：

[1] Univ Cote dAzur, CNRS, Lab Jean Alexandre Dieudonne LJAD, Nice, France

[2] Univ Paris Cite, Sorbonne Univ, CNRS, Lab Jacques Louis Lions LJLL,Inria, Paris, France

[3] Univ Cote dAzur, Lab Elect Antennes & Telecommun LEAT, Nice, France

来源：

2024 IEEE INTERNATIONAL SYMPOSIUM ON ANTENNAS AND PROPAGATION AND INC/USNCURSI RADIO SCIENCE MEETING, AP-S/INC-USNC-URSI 2024 | 2024年

关键词：

D O I：

10.1109/AP-S/INC-USNC-URSI52054.2024.10685863

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

In this paper, a solution for the fast detection of shoulder's tendon injury based on numerical modeling and machine learning (ML) algorithm is proposed. The synthetic data for the ML algorithm are the set of scattering parameters which are produced by solving Maxwell's equations for each transmitting antenna of the microwave imaging (MWI) system. The corresponding data of various healthy and injured models are categorized into two classes. Using support vector machine (SVM) for classification, an accuracy of 100% is achieved.

引用

页码：1511 / 1512

页数：2

共 50 条

[31] SVM-based approach for instrument fault accomodation in automotive systems
Betta, G
Bernieri, A
Capriglione, D
Molinara, M
PROCEEDINGS OF THE 2005 IEEE INTERNATIONAL CONFERENCE ON VIRTUAL ENVIRONMENTS, HUMAN-COMPUTER INTERFACES AND MEASUREMENT SYSTEMS, 2005, : 145 - 150
[32] A SVM-based Parser for Chinese
Chan, Zhimin
Feng, Cheng
ITESS: 2008 PROCEEDINGS OF INFORMATION TECHNOLOGY AND ENVIRONMENTAL SYSTEM SCIENCES, PT 1, 2008, : 1150 - 1156
[33] An SVM-based framework for detecting DoS attacks in virtualized clouds under changing environment
Adel Abusitta
Martine Bellaiche
Michel Dagenais
Journal of Cloud Computing, 7
[34] An SVM-based framework for detecting DoS attacks in virtualized clouds under changing environment
Abusitta, Adel
Bellaiche, Martine
Dagenais, Michel
JOURNAL OF CLOUD COMPUTING-ADVANCES SYSTEMS AND APPLICATIONS, 2018, 7
[35] Intraday volume percentages forecasting using a dynamic SVM-based approach
Xiaotao Liu
Kin Keung Lai
Journal of Systems Science and Complexity, 2017, 30 : 421 - 433
[36] An SVM-based approach for discovering splicing junctions with RNA-Seq
Chu, Chong
Wu, Yufeng
2014 IEEE 4TH INTERNATIONAL CONFERENCE ON COMPUTATIONAL ADVANCES IN BIO AND MEDICAL SCIENCES (ICCABS), 2014,
[37] Intraday Volume Percentages Forecasting Using a Dynamic SVM-Based Approach
LIU Xiaotao
LAI Kin Keung
Journal of Systems Science & Complexity, 2017, 30 (02) : 421 - 433
[38] On the Search of Models for Early Cost Estimates of Bridges: An SVM-Based Approach
Juszczyk, Michal
BUILDINGS, 2020, 10 (01)
[39] Enhanced Android Malware Detection: An SVM-based Machine Learning Approach
Han, Hyoil
Lim, SeungJin
Suh, Kyoungwon
Park, Seonghyun
Cho, Seong-je
Park, Minkyu
2020 IEEE INTERNATIONAL CONFERENCE ON BIG DATA AND SMART COMPUTING (BIGCOMP 2020), 2020, : 75 - 81
[40] Intraday Volume Percentages Forecasting Using a Dynamic SVM-Based Approach
Liu Xiaotao
Lai Kin Keung
JOURNAL OF SYSTEMS SCIENCE & COMPLEXITY, 2017, 30 (02) : 421 - 433

← 1 2 3 4 5 →