Aircraft Detection in Aerial Imagery Based on YOLO Architectures

dc.contributor.authorKashtan, Vita Yu.en
dc.contributor.authorRadionov, Yevhenen
dc.contributor.authorHnatushenko, Volodymyr V.en
dc.date.accessioned2025-07-14T08:46:33Z
dc.date.issued2025
dc.descriptionV. Kashtan: ORCID 0000-0002-0395-5895; Ye. Radionov: ORCID 0009-0002-2839-7161; Vol. Hnatushenko: ORCID 0000-0003-3140-3788en
dc.description.abstractENG: The study is devoted to determining the most efficient YOLO-based architecture for the task of aircraft detection in high-resolution aerial imagery. A comparative analysis was conducted across YOLO models v8 through v11 under three experimental conditions: using pre-trained (raw) models, fine-tuning the models on a domain-specific dataset, and fine-tuning models to a dataset enhanced through a proposed image preprocessing method. The evaluation considered both accuracy and inference performance metrics. The proposed methodology reduced the false negative rate from 19.5% to 3.2% at a confidence threshold of 0.75, underscoring its effectiveness in enhancing target visibility under challenging imaging conditions such as low contrast or background clutter.en
dc.description.sponsorshipDnipro University of Technology, Dniproen
dc.identifier.citationKashtan V., Radionov Ye., Hnatushenko Vol. Aircraft Detection in Aerial Imagery Based on YOLO Architectures. CEUR Workshop Proceedings. Vol. 3983 : Proc. of the Intelligent Systems Workshop at 9th International Conference on Computational Linguistics and Intelligent Systems (CoLInS-2025), Kharkiv, Ukraine, May 15-16, 2025. Kharkiv, 2025. P. 196–208.en
dc.identifier.issn1613-0073
dc.identifier.urihttps://ceur-ws.org/Vol-3983/en
dc.identifier.urihttps://crust.ust.edu.ua/handle/123456789/20791en
dc.language.isoen
dc.publisherCEUR-WS Team, Aachen, Germanyen
dc.subjectmachine learningen
dc.subjectaircraft detectionen
dc.subjectobject detectionen
dc.subjectoptical image preprocessingen
dc.subjectYOLOen
dc.subjectКІТСuk_UA
dc.subject.classificationTECHNOLOGY::Information technology::Image analysisen
dc.titleAircraft Detection in Aerial Imagery Based on YOLO Architecturesen
dc.typeArticleen

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