Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.14365/3531
Full metadata record
DC FieldValueLanguage
dc.contributor.authorTekkok S.C.-
dc.contributor.authorSoyunmez M.E.-
dc.contributor.authorBostanci B.-
dc.contributor.authorEkim P.O.-
dc.date.accessioned2023-06-16T15:00:43Z-
dc.date.available2023-06-16T15:00:43Z-
dc.date.issued2021-
dc.identifier.isbn9.78167E+12-
dc.identifier.urihttps://doi.org/10.1109/HORA52670.2021.9461356-
dc.identifier.urihttps://hdl.handle.net/20.500.14365/3531-
dc.description3rd International Congress on Human-Computer Interaction, Optimization and Robotic Applications, HORA 2021 -- 11 June 2021 through 13 June 2021 -- 171163en_US
dc.description.abstractDue to the COVID-19 pandemic, the face masks are mandatory everywhere so it might be beneficial to automatize the detection and tracking of whether people wear a mask or not with the help of the computer vision. Furthermore, it can be implemented on mobile robots as well. Additionally, face recognition of people is discussed with two different techniques which are based on neural networks and eigenface approach in this study. Hence, a complete system which can be used with mobile platforms has been achieved with the proposed procedure. © 2021 IEEE.en_US
dc.description.sponsorship2200073; Türkiye Bilimsel ve Teknolojik Araştirma Kurumu, TÜBITAKen_US
dc.description.sponsorshipThis research is supported by Scientific and Technological Research Council of Turkey (TUBITAK), project number 2200073.en_US
dc.language.isoenen_US
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.relation.ispartofHORA 2021 - 3rd International Congress on Human-Computer Interaction, Optimization and Robotic Applications, Proceedingsen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectdetectionen_US
dc.subjectneural networksen_US
dc.subjecttrackingen_US
dc.subjectAgricultural robotsen_US
dc.subjectHuman computer interactionen_US
dc.subjectRoboticsen_US
dc.subjectComplete systemen_US
dc.subjectDetection and trackingen_US
dc.subjectEigenface approachen_US
dc.subjectFace masksen_US
dc.subjectMobile platformen_US
dc.subjectFace recognitionen_US
dc.titleFace Detection, Tracking and Recognition with Artificial Intelligenceen_US
dc.typeConference Objecten_US
dc.identifier.doi10.1109/HORA52670.2021.9461356-
dc.identifier.scopus2-s2.0-85114464692en_US
dc.authorscopusid57215421911-
dc.authorscopusid57215409917-
dc.authorscopusid36608964400-
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.identifier.scopusqualityN/A-
dc.identifier.wosqualityN/A-
item.grantfulltextreserved-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.cerifentitytypePublications-
item.openairetypeConference Object-
item.fulltextWith Fulltext-
item.languageiso639-1en-
Appears in Collections:Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
Files in This Item:
File SizeFormat 
2622.pdf
  Restricted Access
6.59 MBAdobe PDFView/Open    Request a copy
Show simple item record



CORE Recommender

SCOPUSTM   
Citations

2
checked on Oct 2, 2024

Page view(s)

74
checked on Sep 30, 2024

Google ScholarTM

Check




Altmetric


Items in GCRIS Repository are protected by copyright, with all rights reserved, unless otherwise indicated.