Publication:
Covid-19 X-ray image classification using SVM based on local binary pattern

dc.contributor.authorDURU, ADİL DENİZ
dc.contributor.authorsAl-Jumaili S., Al-Azzawi A., DURU A. D. , Ibrahim A. A.
dc.date.accessioned2022-10-04T11:04:38Z
dc.date.accessioned2026-01-11T11:17:16Z
dc.date.available2022-10-04T11:04:38Z
dc.date.issued2021-01-01
dc.description.abstract© 2021 IEEE.Coronavirus usually transmits from the animal to the human, but now, the virus transmission is between persons. Therefore, scientists and researchers are trying to develop several types of machine learning methods to defend against COVID-19. Medical images play a significant role in this time due to they can be used to recognize COVID-19 accurately. However, in this paper, we used X-Ray images, the images undergone to sharpening techniques to increase the results further. The texture techniques named local binary pattern (LBP) have been used in order to extract features. The features obtained were applied to the support vector machine (SVM). The results we achieved were 100% for all performance measurements. Our results were conspicuously superior compared to the state-of-the-art papers published.
dc.identifier.citationAl-Jumaili S., Al-Azzawi A., DURU A. D. , Ibrahim A. A. , \"Covid-19 X-ray image classification using SVM based on Local Binary Pattern\", 5h International Symposium on Multidisciplinary Studies and Innovative Technologies, ISMSIT 2021, Ankara, Türkiye, 21 - 23 Ekim 2021, ss.383-387
dc.identifier.doi10.1109/ismsit52890.2021.9604731
dc.identifier.endpage387
dc.identifier.startpage383
dc.identifier.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85123319534&origin=inward
dc.identifier.urihttps://hdl.handle.net/11424/282070
dc.language.isoeng
dc.relation.ispartof5h International Symposium on Multidisciplinary Studies and Innovative Technologies, ISMSIT 2021
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectSosyal ve Beşeri Bilimler
dc.subjectSosyoloji
dc.subjectKütüphanecilik
dc.subjectHarita Mühendisliği-Geomatik
dc.subjectBilgi Sistemleri, Haberleşme ve Kontrol Mühendisliği
dc.subjectKontrol ve Sistem Mühendisliği
dc.subjectBilgisayar Bilimleri
dc.subjectAlgoritmalar
dc.subjectMühendislik ve Teknoloji
dc.subjectSocial Sciences and Humanities
dc.subjectSociology
dc.subjectLibrary Sciences
dc.subjectGeotechnical Engineering
dc.subjectInformation Systems, Communication and Control Engineering
dc.subjectControl and System Engineering
dc.subjectComputer Sciences
dc.subjectalgorithms
dc.subjectEngineering and Technology
dc.subjectMühendislik, Bilişim ve Teknoloji (ENG)
dc.subjectSosyal Bilimler (SOC)
dc.subjectBilgisayar Bilimi
dc.subjectMühendislik
dc.subjectSosyal Bilimler Genel
dc.subjectOTOMASYON & KONTROL SİSTEMLERİ
dc.subjectBİLGİSAYAR BİLİMİ, YAPAY ZEKA
dc.subjectTELEKOMÜNİKASYON
dc.subjectALETLER & GÖSTERİM
dc.subjectMÜHENDİSLİK, MULTİDİSİPLİNER
dc.subjectMÜHENDİSLİK, ÜRETİM
dc.subjectBİLGİ BİLİMİ VE KÜTÜPHANE BİLİMİ
dc.subjectEngineering, Computing & Technology (ENG)
dc.subjectSocial Sciences (SOC)
dc.subjectCOMPUTER SCIENCE
dc.subjectENGINEERING
dc.subjectSOCIAL SCIENCES, GENERAL
dc.subjectAUTOMATION & CONTROL SYSTEMS
dc.subjectCOMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
dc.subjectTELECOMMUNICATIONS
dc.subjectINSTRUMENTS & INSTRUMENTATION
dc.subjectENGINEERING, MULTIDISCIPLINARY
dc.subjectENGINEERING, MANUFACTURING
dc.subjectINFORMATION SCIENCE & LIBRARY SCIENCE
dc.subjectMedya Teknolojisi
dc.subjectFizik Bilimleri
dc.subjectKontrol ve Optimizasyon
dc.subjectEnstrümantasyon
dc.subjectEmniyet, Risk, Güvenilirlik ve Kalite
dc.subjectYapay Zeka
dc.subjectBilgisayar Ağları ve İletişim
dc.subjectBilgisayar Bilimi Uygulamaları
dc.subjectBilgi Sistemleri ve Yönetimi
dc.subjectSosyal Bilimler ve Beşeri Bilimler
dc.subjectMedia Technology
dc.subjectPhysical Sciences
dc.subjectControl and Optimization
dc.subjectInstrumentation
dc.subjectSafety, Risk, Reliability and Quality
dc.subjectArtificial Intelligence
dc.subjectComputer Networks and Communications
dc.subjectComputer Science Applications
dc.subjectInformation Systems and Management
dc.subjectSocial Sciences & Humanities
dc.titleCovid-19 X-ray image classification using SVM based on local binary pattern
dc.typeconferenceObject
dspace.entity.typePublication

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