Microemboli classification using non-linear kernel support vector machines and RF signals
Joint Authors
Ferroudji, Karim
Benoudjit, Nabil
Bouakaz, Ayyash
Source
Journal of Automation and Systems Engineering
Issue
Vol. 6, Issue 3 (30 Sep. 2012), pp.123-132, 10 p.
Publisher
Publication Date
2012-09-30
Country of Publication
Algeria
No. of Pages
10
Main Subjects
Engineering & Technology Sciences (Multidisciplinary)
Topics
Abstract EN
Man's intelligent behavior is due in part to his ability to select, classify, and abstract significant information reaching him from his environment by way of his senses.
This function, pattern recognition, has become a major focus of research by scientists working in the field of artificial intelligence.
Due to its clinical importance, several classification methods have been studied for micro emboli detection and characterization.
In the human body ; emboli can produce severe damage like stroke or heart attack thus the importance of an automatic classification system.
In this paper, we propose a new approach to detect and classify micro emboli using support vector machine and the backscatter Radio-Frequency (RF) signal.
This short communication demonstrates the opportunity to classify emboli based on a RF signals and support vector machine ; the classification rates reached 96.42 %..
American Psychological Association (APA)
Ferroudji, Karim& Benoudjit, Nabil& Bouakaz, Ayyash. 2012. Microemboli classification using non-linear kernel support vector machines and RF signals. Journal of Automation and Systems Engineering،Vol. 6, no. 3, pp.123-132.
https://search.emarefa.net/detail/BIM-328800
Modern Language Association (MLA)
Ferroudji, Karim…[et al.]. Microemboli classification using non-linear kernel support vector machines and RF signals. Journal of Automation and Systems Engineering Vol. 6, no. 3 (Sep. 2012), pp.123-132.
https://search.emarefa.net/detail/BIM-328800
American Medical Association (AMA)
Ferroudji, Karim& Benoudjit, Nabil& Bouakaz, Ayyash. Microemboli classification using non-linear kernel support vector machines and RF signals. Journal of Automation and Systems Engineering. 2012. Vol. 6, no. 3, pp.123-132.
https://search.emarefa.net/detail/BIM-328800
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references : p. 131-132
Record ID
BIM-328800