PROHIBITED ZONE INTRUSION DETECTION

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dc.contributor.authorBicakci, Sukru
dc.contributor.authorAksuren, Ibrahim Gokhan
dc.contributor.authorHocaoglu, Ali Koksal
dc.date.accessioned2025-10-29T11:36:40Z
dc.date.issued2018
dc.departmentGebze Teknik Üniversitesi
dc.description26th IEEE Signal Processing and Communications Applications Conference (SIU) -- MAY 02-05, 2018 -- Izmir, TURKEY
dc.description.abstractIn this study, using surveillance videos, an intrusion detection to prohibited zone algorithm is developed. The forbidden zone determined by the operator was classified using the support vector machine classifier and intrusion detection was performed. For training the classifier, positive samples are selected by the operator. Proposed algorithm further reduces the false alarms with respect to the existing methods.
dc.description.sponsorshipIEEE,Huawei,Aselsan,NETAS,IEEE Turkey Sect,IEEE Signal Proc Soc,IEEE Commun Soc,ViSRATEK,Adresgezgini,Rohde & Schwarz,Integrated Syst & Syst Design,Atilim Univ,Havelsan,Izmir Katip Celebi Univ
dc.identifier.isbn978-1-5386-1501-0
dc.identifier.issn2165-0608
dc.identifier.orcid0000-0002-2285-0677
dc.identifier.scopus2-s2.0-85050810793
dc.identifier.scopusqualityN/A
dc.identifier.urihttps://hdl.handle.net/20.500.14854/13407
dc.identifier.wosWOS:000511448500384
dc.identifier.wosqualityN/A
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isotr
dc.publisherIEEE
dc.relation.ispartof2018 26th Signal Processing and Communications Applications Conference (Siu)
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_WOS_20251020
dc.subjectIntrusion Dedection
dc.subjectHistogram of Oriented Gradients (HOG)
dc.subjectSupport Vector Machine (SVM)
dc.subjectMachine Learning
dc.titlePROHIBITED ZONE INTRUSION DETECTION
dc.typeConference Object

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