Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.13091/2379
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dc.contributor.authorÖrnek, Ahmet Haydar-
dc.contributor.authorÇelik, Mustafa-
dc.contributor.authorAlper, Ozan Can-
dc.date.accessioned2022-05-23T20:07:30Z-
dc.date.available2022-05-23T20:07:30Z-
dc.date.issued2021-
dc.identifier.isbn9781665442312-
dc.identifier.urihttps://doi.org/10.1109/ICECET52533.2021.9698252-
dc.identifier.urihttps://hdl.handle.net/20.500.13091/2379-
dc.description2021 International Conference on Electrical, Computer, and Energy Technologies, ICECET 2021 -- 9 December 2021 through 10 December 2021 -- -- 177176en_US
dc.description.abstractIn order to realize real-time computer vision projects we need to avoid time consuming operations such as more inference for deep learning. Our current application uses face images to decide whether there is a mask on the face so as to prevent unhealthy situations in view of epidemic. Since frames are sequentially coming it is necessary to eliminate similar frames to avoid more inference. We show how to measure a similarity between two frames by comparing traditional and deep learning based methods in this study. This study shows that deep learning based method is more efficient than traditional methods when comparing images. © 2021 IEEE.en_US
dc.description.sponsorshipThis study was supported by ”Epidemic Prevention System” project of Huawei Turkey R&D Center.en_US
dc.language.isoenen_US
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.relation.ispartofInternational Conference on Electrical, Computer, and Energy Technologies, ICECET 2021en_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectdeep learningen_US
dc.subjectimage similarityen_US
dc.subjectreal-world applicationsen_US
dc.subjectDeep learningen_US
dc.subject'currenten_US
dc.subjectDeep learningen_US
dc.subjectFace imagesen_US
dc.subjectImage similarityen_US
dc.subjectLearning-based methodsen_US
dc.subjectReal-time computer visionen_US
dc.subjectReal-worlden_US
dc.subjectReal-world applicationen_US
dc.subjectImage analysisen_US
dc.titleComparing Image Similarity Methods for Face Imagesen_US
dc.typeConference Objecten_US
dc.identifier.doi10.1109/ICECET52533.2021.9698252-
dc.identifier.scopus2-s2.0-85127068598en_US
dc.departmentFakülteler, Mühendislik ve Doğa Bilimleri Fakültesi, Elektrik-Elektronik Mühendisliği Bölümüen_US
dc.identifier.wosWOS:000814669100269en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.authorscopusid57210593918-
dc.authorscopusid57457105000-
dc.authorscopusid57551207200-
item.grantfulltextembargo_20300101-
item.openairetypeConference Object-
item.fulltextWith Fulltext-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.languageiso639-1en-
item.cerifentitytypePublications-
Appears in Collections:Mühendislik ve Doğa Bilimleri Fakültesi Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collections
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collections
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