Performance Comparison of Faster R-CNN and SSD in Vehicle Detection from Aerial Traffic Videos

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dc.contributor.authorSermsar, Funda
dc.contributor.authorMoghadam, Mahrus Thabit
dc.contributor.authorKoca, Merve
dc.date.accessioned2025-03-17T12:22:47Z
dc.date.available2025-03-17T12:22:47Z
dc.date.issued2024
dc.departmentTarsus Üniversitesi
dc.descriptionIEEE SMC; IEEE Turkiye Section
dc.description2024 Innovations in Intelligent Systems and Applications Conference, ASYU 2024 -- 16 October 2024 through 18 October 2024 -- Ankara -- 204562
dc.description.abstractVehicle detection is essential for urban planning, traffic management, and various security and surveillance applications. This study compares the performance of two popular deep learning algorithms, Faster R-CNN and SSD, for vehicle detection using traffic video recordings obtained from unmanned aerial vehicles. The dataset, comprising images taken from diverse angles, heights, and lighting conditions, was utilized to assess the effectiveness of both models. Faster R-CNN demonstrated superior accuracy in detecting vehicles and motorcycles under various conditions, including night scenarios and scenes with obstacles such as shadows, traffic signs, and light poles. However, it struggled with detecting very small objects and those with color tones similar to the background. In contrast, while SSD performed well under optimal lighting, it exhibited limitations in detecting smaller vehicles partially obscured by environmental elements. Quantitative analysis revealed that Faster R-CNN had 13.21% higher precision, 12.5% higher recall, and 10.04% higher mAP compared to SSD. Despite its superior detection performance, Faster R-CNN's longer detection time indicates that SSD may be more suitable for real-time applications where speed is crucial. © 2024 IEEE.
dc.identifier.doi10.1109/ASYU62119.2024.10757013
dc.identifier.isbn979-835037943-3
dc.identifier.scopus2-s2.0-85213310152
dc.identifier.scopusqualityN/A
dc.identifier.urihttps://doi.org/10.1109/ASYU62119.2024.10757013
dc.identifier.urihttps://hdl.handle.net/20.500.13099/1386
dc.indekslendigikaynakScopus
dc.language.isotr
dc.publisherInstitute of Electrical and Electronics Engineers Inc.
dc.relation.ispartof2024 Innovations in Intelligent Systems and Applications Conference, ASYU 2024
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_Scopus_20250316
dc.subjectautomated traffic management
dc.subjectFaster R-CNN
dc.subjectSSD
dc.subjectvehicle detection
dc.titlePerformance Comparison of Faster R-CNN and SSD in Vehicle Detection from Aerial Traffic Videos
dc.title.alternativeHavadan Trafik Videolarından Taşıt Tespitinde Faster R-CNN ve SSD'nin Performans Kıyaslaması
dc.typeConference Object

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