Microwave Stroke Detection and Classification Using Different Methods from MATLAB’s Classification Learner Toolbox
- Resource Type
- Conference
- Authors
- Pokorny, Tomas; Tesarik, Jan
- Source
- 2019 European Microwave Conference in Central Europe (EuMCE) European Microwave Conference in Central Europe (EuMCE), 2019. :500-503 May, 2019
- Subject
- Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Fields, Waves and Electromagnetics
Photonics and Electrooptics
Classification algorithms
Microwave imaging
Microwave theory and techniques
Support vector machines
Microwave measurement
Phantoms
Hemorrhaging
Support Vector Machines
MATLAB
- Language
In this work, performance of 5 different supervised learning algorithms from MATLAB Classification learner toolbox for microwave stroke detection and classification was tested and the suitability of the algorithms were compared. For this purpose, training and test data were obtained using a 2D microwave imaging system and reconfigurable head phantom.