Derin öğrenme tabanlı YOLOv5 nesne tespiti yöntemi kullanılarak gaz tüpü tespiti

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dc.contributor.authorAlbayrak, Abdulkadir
dc.contributor.authorÖzerdem, Mehmet Siraç
dc.date.accessioned2024-04-24T17:56:28Z
dc.date.available2024-04-24T17:56:28Z
dc.date.issued2022
dc.departmentDicle Üniversitesi, Mühendislik Fakültesi, Elektrik ve Elektronik Mühendisliği Bölümüen_US
dc.description7th International Conference on Computer Science and Engineering, UBMK 2022 -- 14 September 2022 through 16 September 2022 -- -- 183844en_US
dc.description.abstractDetection and tracking of objects has critical importance in terms of speeding up the process and facilitating the work in many areas. Especially in the process of counting objects, which is difficult and time-consuming for experts. In this paper, a study was carried out to detect gas cylinders with different colors and shapes using the deep learning-based Yolov5 method. The process of counting cylinders in the stock area or in the filling facilities can be difficult for the specialist due to the different sizes, arrangement and large number of cylinders. Within the scope of the study, a data set containing different types of cylinders in gas filling facilities was created. When the obtained results are evaluated, it has been observed that the Yolov5 algorithm detects the gas cylinders with different color and shape properties with a high success rate of 96.16%. In addition to the detection success, it has been observed that the method is also successful in different objective detections such as precision, sensitivity and box intersection.en_US
dc.identifier.citationAlbayrak, A. ve Özerdem, M. S. (2022). Gas cylinder detection using deep learning based YOLOv5 object detection method. Proceedings - 7th International Conference on Computer Science and Engineering, UBMK 2022, 434-437.
dc.identifier.doi10.1109/UBMK55850.2022.9919478
dc.identifier.endpage437en_US
dc.identifier.isbn9781665470100
dc.identifier.scopus2-s2.0-85141824660en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.startpage434en_US
dc.identifier.urihttps://doi.org/10.1109/UBMK55850.2022.9919478
dc.identifier.urihttps://hdl.handle.net/11468/23527
dc.indekslendigikaynakScopusen_US
dc.language.isotren_US
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.relation.ispartofProceedings - 7th International Conference on Computer Science and Engineering, UBMK 2022en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectDeep learningen_US
dc.subjectGas cylinder detectionen_US
dc.subjectObject detectionen_US
dc.subjectYolov5en_US
dc.titleDerin öğrenme tabanlı YOLOv5 nesne tespiti yöntemi kullanılarak gaz tüpü tespitien_US
dc.title.alternativeGas Cylinder Detection Using Deep Learning Based YOLOv5 Object Detection Methoden_US
dc.typeConference Objecten_US

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