Vehicle Color-Type Detection Based on YOLOv8 and K-Means
| dc.contributor.author | Çiçek, İrem | |
| dc.contributor.author | Apaydın, Nafiye Nur | |
| dc.contributor.author | Kılıç, İrfan | |
| dc.contributor.author | Yaman, Orhan | |
| dc.contributor.author | Karaköse, Mehmet | |
| dc.date.accessioned | 2026-09-08T07:04:20Z | |
| dc.date.issued | 2026 | |
| dc.department | Fırat Üniveristesi | |
| dc.description | Grant No: 5220154 | |
| dc.description.abstract | There is provided a computing device for managing honeybee colonies for pollination of crop(s), comprises: a processor(s) configured for: for each one of a plurality of honeybee colonies positioned for pollination of crop(s) in a geographical area: obtaining in-colony feature(s), computed based on output of internal sensor(s) monitoring the honeybee colony, wherein the in-colony feature(s) is indicative of an internal state of the honeybee colony positioned for pollination of crop(s) in the geographical area, obtaining out-colony feature(s), computed based on output of external sensor(s) monitoring the environment of the honeybee colony, wherein the out-colony feature is indicative of an external environment of the honeybee colony, feeding a combination of the in-colony feature(s) and the out-colony feature(s) into a machine learning model, and obtaining an outcome indicating pollination effectiveness of the honeybee colony. | |
| dc.description.sponsorship | TUBITAK (The Scientific and Technological Research Council of Turkey) under | |
| dc.identifier.dergipark | 1951468 | |
| dc.identifier.doi | 10.54565/jphcfum.1951468 | |
| dc.identifier.endpage | 95 | |
| dc.identifier.issn | 2651-3080 | |
| dc.identifier.issue | 1 | |
| dc.identifier.orcid | 0009-0001-4932-8969 | |
| dc.identifier.orcid | 0009-0006-3438-7401 | |
| dc.identifier.orcid | 0000-0001-5079-2825 | |
| dc.identifier.orcid | 0000-0001-9623-2284 | |
| dc.identifier.orcid | 0000-0002-3276-3788 | |
| dc.identifier.startpage | 87 | |
| dc.identifier.uri | https://doi.org/10.54565/jphcfum.1951468 | |
| dc.identifier.uri | https://hdl.handle.net/11508/64681 | |
| dc.identifier.volume | 9 | |
| dc.language.iso | en | |
| dc.publisher | Niyazi BULUT | |
| dc.relation.ispartof | Journal of Physical Chemistry and Functional Materials | |
| dc.relation.publicationcategory | Makale - Ulusal Hakemli Dergi - Kurum Öğretim Elemanı | |
| dc.rights | info:eu-repo/semantics/openAccess | |
| dc.snmz | KA_DergiPark_20250903 | |
| dc.subject | Vehicle color and type detections | |
| dc.subject | Traffic Road Object Detection Dataset | |
| dc.subject | YOLOv8 | |
| dc.subject | K-Means | |
| dc.title | Vehicle Color-Type Detection Based on YOLOv8 and K-Means | |
| dc.type | Article |







