| dc.contributor.author | Gilik, Ayşenur | |
| dc.contributor.author | Demir, Kubilay | |
| dc.contributor.author | Özmen, Atilla | |
| dc.date.accessioned | 2020-12-20T19:56:09Z | |
| dc.date.available | 2020-12-20T19:56:09Z | |
| dc.date.issued | 2018 | |
| dc.identifier.issn | 2165-0608 | en_US |
| dc.identifier.uri | https://hdl.handle.net/20.500.12469/3614 | |
| dc.description.abstract | In this study, a system has been developed to detect the human density of indoor spaces such as libraries, banks, shopping malls. The RGB images used in this work was obtained from the real-life space. First and second order color moments were used as feature extractor. | en_US |
| dc.language.iso | tur | en_US |
| dc.publisher | IEEE | en_US |
| dc.rights | info:eu-repo/semantics/closedAccess | en_US |
| dc.subject | RGB images | en_US |
| dc.subject | Detection the density | en_US |
| dc.subject | Indoor space | en_US |
| dc.subject | Statistical color moments | en_US |
| dc.title | RGB Color Based Occupancy Rate Detection of Indoor Spaces | en_US |
| dc.type | conferenceObject | en_US |
| dc.relation.journal | 2018 | en_US |
| dc.identifier.issue | 2018 26th Signal Processing and Communications Applications Conference (SIU) | en_US |
| dc.department | Fakülteler, Mühendislik ve Doğa Bilimleri Fakültesi, Elektrik-Elektronik Mühendisliği Bölümü | en_US |
| dc.identifier.wos | WOS:000511448500633 | en_US |
| dc.institutionauthor | Gilik, Ayşenur | en_US |
| dc.institutionauthor | Demir, Kubilay | en_US |
| dc.institutionauthor | Özmen, Atilla | en_US |
| dc.relation.publicationcategory | Konferans Öğesi - Uluslararası - Kurum Öğretim Elemanı | en_US |
