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dc.contributor.authorKAYABOL, KORAY
dc.contributor.authorAkan, Aydin
dc.contributor.authorKutluk, Sezer
dc.date.accessioned2021-03-03T17:35:32Z
dc.date.available2021-03-03T17:35:32Z
dc.identifier.citationKutluk S., KAYABOL K., Akan A., "A Probabilistic Method for the Classification of Hyperspectral Images", 24th Signal Processing and Communication Application Conference (SIU), Zonguldak, Türkiye, 16 - 19 Mayıs 2016, ss.905-908
dc.identifier.otherav_4a746bc3-0c7f-4d1b-8cb6-dfb0121a28bb
dc.identifier.othervv_1032021
dc.identifier.urihttp://hdl.handle.net/20.500.12627/53493
dc.identifier.urihttps://doi.org/10.1109/siu.2016.7495887
dc.description.abstractIn this study a supervised classification and dimensionality reduction method for hyperspectral images is proposed. For this purpose, using probabilistic principal component analysis (PPCA), dimensionality reduction is performed and a Gaussian mixture model (GMM) is built. Alongside this mixture model, spatial information is also included into the classification process by taking advantage of pixel neighborhoods.
dc.language.isoeng
dc.subjectSinyal İşleme
dc.subjectMühendislik ve Teknoloji
dc.subjectMÜHENDİSLİK, ELEKTRİK VE ELEKTRONİK
dc.subjectMühendislik
dc.subjectMühendislik, Bilişim ve Teknoloji (ENG)
dc.subjectBilgi Sistemleri, Haberleşme ve Kontrol Mühendisliği
dc.titleA Probabilistic Method for the Classification of Hyperspectral Images
dc.typeBildiri
dc.contributor.departmentGebze Teknik Üniversitesi , ,
dc.contributor.firstauthorID148542


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