Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/6566
Title: Doppler ultrasound signals analysis using multiclass support vector machines with error correcting output codes
Authors: Übeyli, Elif Derya
Keywords: multiclass support vector machine (SVM)
wavelet coefficients
Doppler ultrasound signals
Issue Date: 2007
Publisher: Pergamon-Elsevier Science Ltd
Abstract: In this paper, the multiclass support vector machines (SVMs) with the error correcting output codes (ECOC) were presented for the multiclass Doppler ultrasound signals (ophthalmic arterial Doppler signals and internal carotid arterial Doppler signals) classification problems. Decision making was performed in two stages: feature extraction by computing the wavelet coefficients and classification using the classifier trained on the extracted features. The purpose was to determine an optimum classification scheme for this problem and also to infer clues about the extracted features. The present research demonstrated that the wavelet coefficients are the features which well represent the studied Doppler ultrasound signals and the multiclass SVMs trained on these features achieved high classification accuracies. (c) 2006 Elsevier Ltd. All rights reserved.
URI: https://doi.org/10.1016/j.eswa.2006.06.008
https://hdl.handle.net/20.500.11851/6566
ISSN: 0957-4174
Appears in Collections:Elektrik ve Elektronik Mühendisliği Bölümü / Department of Electrical & Electronics Engineering
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

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