Image segmentation applications with unsupervised neural networks

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dc.contributor.authorŞengür, Abdulkadir
dc.contributor.authorTürko?lu, Ibrahim
dc.contributor.authorInce, M. Cevdet
dc.date.accessioned2026-08-12T16:10:00Z
dc.date.issued2005
dc.departmentFırat Üniversitesi
dc.descriptionIEEE 13th Signal Processing and Communications Applications Conference, SIU 2005 -- 16 May 2005 through 18 May 2005 -- Kayseri -- 69003
dc.description.abstractImage segmentation is the most difficult task of low level computer vision applications. The performance of the segmentation algorithm affects the subsequent applications performances such as high level pattern recognition applications. In this study we examine 1-D and 2-D unsupervised artificial neural networks (Kohonen network) and we evaluate the performances of the examined structures over image segmentation applications. Experimental studies show the advantages and disadvantages of the Kohonen networks. © 2005 IEEE.
dc.identifier.doi10.1109/SIU.2005.1567673
dc.identifier.endpage274
dc.identifier.isbn0780392396
dc.identifier.isbn978-078039239-7
dc.identifier.scopus2-s2.0-33846585079
dc.identifier.scopusqualityN/A
dc.identifier.startpage271
dc.identifier.urihttps://doi.org/10.1109/SIU.2005.1567673
dc.identifier.urihttps://hdl.handle.net/11508/41699
dc.identifier.volume2005
dc.indekslendigikaynakScopus
dc.language.isotr
dc.relation.ispartofProceedings of the IEEE 13th Signal Processing and Communications Applications Conference, SIU 2005
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_Scopus_20260511
dc.subjectAlgorithms; Computer vision; Image segmentation; Pattern recognition; Segmentation algorithms; Neural networks
dc.titleImage segmentation applications with unsupervised neural networks
dc.title.alternativeE?iticisiz yapay sinir aglari ile görüntü bölütleme uygulamalari
dc.typeConference Object

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