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Categorizing sequences of laryngeal data for decision support
Kaunas University of Technology, Lithuania.
Kaunas University of Technology, Lithuania.
Kaunas University of Technology, Lithuania.
Kaunas University of Technology, Lithuania.
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2009 (Engelska)Ingår i: Electrical and Control Technologies: Proceedings of the 4th international conference, ECT 2009 / [ed] A. Navickas (general editor), A. Sauhats, A. Virbalis, M. Ažubalis, V. Galvanauskas, A. Jonaitis, Kaunas: IFAC Committee of National Lithuanian Organisation , 2009, s. 99-102Konferensbidrag, Publicerat paper (Refereegranskat)
Abstract [en]

This paper is concerned with kernel-based techniques forcategorizing laryngeal disorders based on information extracted fromsequences of laryngeal colour images. The features used tocharacterize a laryngeal image are given by the kernel principalcomponents computed using the $N$-vector of the 3-D colourhistogram. The least squares support vector machine (LS-SVM) isdesigned for categorizing an image sequence into the healthy, nodular and diffuse classes. The kernel functionemployed by the SVM classifier is defined over a pair of matrices, rather than over a pair of vectors. An encouraging classificationperformance was obtained when testing the developed tools on datarecorded during routine laryngeal videostroboscopy.

Ort, förlag, år, upplaga, sidor
Kaunas: IFAC Committee of National Lithuanian Organisation , 2009. s. 99-102
Serie
Electrical and Control Technologies, ISSN 1822-5934 ; 2009
Nyckelord [en]
Larynx pathology, Image sequence, Classification, Support vector machine
Nationell ämneskategori
Data- och informationsvetenskap
Identifikatorer
URN: urn:nbn:se:hh:diva-108OAI: oai:DiVA.org:hh-108DiVA, id: diva2:236173
Konferens
Electrical and Control Technologies: proceedings of the 4th international conference, ECT 2009, May 7 - 8, Kaunas, Lithuania
Tillgänglig från: 2009-09-21 Skapad: 2009-09-21 Senast uppdaterad: 2018-01-13Bibliografiskt granskad

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http://www.elektroklubas.lt/pdf/2009/Proceedings_ECT-2009_EN.pdf

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