Face Detection, Tracking and Recognition With Artificial Intelligence
| dc.contributor.author | Tekkok S.C. | |
| dc.contributor.author | Soyunmez M.E. | |
| dc.contributor.author | Bostanci B. | |
| dc.contributor.author | Ekim P.O. | |
| dc.date.accessioned | 2023-06-16T15:00:43Z | |
| dc.date.available | 2023-06-16T15:00:43Z | |
| dc.date.issued | 2021 | |
| dc.description | 3rd International Congress on Human-Computer Interaction, Optimization and Robotic Applications, HORA 2021 -- 11 June 2021 through 13 June 2021 -- 171163 | en_US |
| dc.description.abstract | Due 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.sponsorship | 2200073; Türkiye Bilimsel ve Teknolojik Araştirma Kurumu, TÜBITAK | en_US |
| dc.description.sponsorship | This research is supported by Scientific and Technological Research Council of Turkey (TUBITAK), project number 2200073. | en_US |
| dc.identifier.doi | 10.1109/HORA52670.2021.9461356 | |
| dc.identifier.isbn | 9.78E+12 | |
| dc.identifier.scopus | 2-s2.0-85114464692 | |
| dc.identifier.uri | https://doi.org/10.1109/HORA52670.2021.9461356 | |
| dc.identifier.uri | https://hdl.handle.net/20.500.14365/3531 | |
| dc.language.iso | en | en_US |
| dc.publisher | Institute of Electrical and Electronics Engineers Inc. | en_US |
| dc.relation.ispartof | HORA 2021 - 3rd International Congress on Human-Computer Interaction, Optimization and Robotic Applications, Proceedings | en_US |
| dc.rights | info:eu-repo/semantics/closedAccess | en_US |
| dc.subject | detection | en_US |
| dc.subject | neural networks | en_US |
| dc.subject | tracking | en_US |
| dc.subject | Agricultural robots | en_US |
| dc.subject | Human computer interaction | en_US |
| dc.subject | Robotics | en_US |
| dc.subject | Complete system | en_US |
| dc.subject | Detection and tracking | en_US |
| dc.subject | Eigenface approach | en_US |
| dc.subject | Face masks | en_US |
| dc.subject | Mobile platform | en_US |
| dc.subject | Face recognition | en_US |
| dc.title | Face Detection, Tracking and Recognition With Artificial Intelligence | en_US |
| dc.type | Conference Object | en_US |
| dspace.entity.type | Publication | |
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| gdc.description.departmenttemp | Tekkok, S.C., Izmir University of Economics, Electrical and Electronics Engineering Department, Izmir, Turkey; Soyunmez, M.E., Izmir University of Economics, Electrical and Electronics Engineering Department, Izmir, Turkey; Bostanci, B., Izmir University of Economics, Electrical and Electronics Engineering Department, Izmir, Turkey; Ekim, P.O., Izmir University of Economics, Electrical and Electronics Engineering Department, Izmir, Turkey | en_US |
| gdc.description.endpage | 5 | |
| gdc.description.publicationcategory | Konferans Öğesi - Uluslararası - Kurum Öğretim Elemanı | en_US |
| gdc.description.scopusquality | N/A | |
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| gdc.virtual.author | Oğuz Ekim, Pınar | |
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