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dc.contributor.authorKeskenler, Mustafa Furkan
dc.contributor.authorHasiloğlu, Abdulsamet
dc.contributor.authorÖzyer, Gülşah Tumuklu
dc.contributor.authorÖzyer, Barış
dc.contributor.authorŞimşek, Emrah
dc.date.accessioned2020-12-19T19:40:40Z
dc.date.available2020-12-19T19:40:40Z
dc.date.issued2019
dc.identifier.citationKeskenler, M.F., Hasiloğlu, A., Özyer, G.T., Özyer, B. & Şimşek, E. (2019). Sperm Detection and Analysis Using Feature Description Algorithms. 2019 27Th Signal Processing and Communications Applications Conference (Siu). http://doi.org/10.1109/SIU.2019.8806287en_US
dc.identifier.isbn978-1-7281-1904-5
dc.identifier.issn2165-0608
dc.identifier.urihttps://hdl.handle.net/11436/1619
dc.identifier.urihttp://doi.org/10.1109/SIU.2019.8806287en_US
dc.description27th Signal Processing and Communications Applications Conference (SIU) -- APR 24-26, 2019 -- Sivas Cumhuriyet Univ, Sivas, TURKEYen_US
dc.descriptionHasiloglu, Abdulsamet/0000-0002-0963-825Xen_US
dc.descriptionWOS: 000518994300032en_US
dc.description.abstractComputer aided sperm analysis (CASA) systems have been used in recent years to examine the mobility and morphology of human and animal sperm. While these systems detect sperm, they fail to detect more than one sperm image coinciding or overlapping between the motile spermatozoa. in addition, sensitive results can not be obtained against the light factor of the background in sperm detection. in order to improve the above mentioned problems, using the random forest algorithm, sperm detection was performed on the images obtained from the HOG, LBP and color histogram feature extraction methods. When the experimental results were examined, it was observed that 92% success rate was achieved in the images.en_US
dc.description.sponsorshipIEEE Turkey Sect, Turkcell, Turkhavacilik Uzaysanayii, Turitak Bilgem, Gebze Teknik Univ, SAP, Detaysoft, NETAS, Havelsanen_US
dc.language.isoturen_US
dc.publisherIeeeen_US
dc.relation.ispartofseriesSignal Processing and Communications Applications Conference
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectSperm detectionen_US
dc.subjectColor histogramen_US
dc.subjectHOGen_US
dc.subjectLBPen_US
dc.subjectRandom foresten_US
dc.titleSperm detection and analysis using feature description algorithmsen_US
dc.typeconferenceObjecten_US
dc.contributor.departmentRTEÜ, Mühendislik ve Mimarlık Fakültesi, Bilgisayar Mühendisliği Bölümüen_US
dc.contributor.institutionauthorŞimşek, Emrah
dc.identifier.doi10.1109/SIU.2019.8806287en_US
dc.relation.journal2019 27Th Signal Processing and Communications Applications Conference (Siu)en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US


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