Acta Infologica

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Research Article


DOI :10.26650/acin.1273088   IUP :10.26650/acin.1273088    Full Text (PDF)

Vision-Based Amateur Drone Detection: Performance Analysis of New Approaches in Deep Learning

Ahmet Aydın, Tarık Talan, Cemal Aktürk

Interest in unmanned aerial vehicles (UAVs) has increased significantly. UAVs capable of autonomous operations have expanded their application areas as they can be easily deployed in various fields. The expansion of UAVs’ areas of operation also brings safety issues. Although legally prohibited places forUAV flights are defined, measures should be taken to detect violations. This study tested recently proposed methods that are used to detect objects from images on UV images, and their performances were discussed. We tested the models on a new dataset named GDrone that we created by collecting various images of drones. Two tested models, YOLOv6 and YOLOv7, have never been tested with a drone dataset. According to the experimental tests, the most successful model was YOLOv7 architecture, and its mAP (mean Average Precision) was 95.8% on GDrone dataset.

Keywords: Unmanned aerial vehicles, amateur drone detection, convolutional neural networks, UAW dataset
DOI :10.26650/acin.1273088   IUP :10.26650/acin.1273088    Full Text (PDF)

Görüntü Tabanlı Amatör Drone Tespiti: Derin Öğrenmede Yeni Yaklaşımların Performans Analizi

Ahmet Aydın, Tarık Talan, Cemal Aktürk

İnsansız hava araçlarına (İHA) olan ilgi önemli ölçüde artmıştır. Otonom çalışabilen İHA’lar, çeşitli alanlara kolaylıkla konuşlandırılabilmeleri nedeniyle uygulama alanlarını genişletmiştir. İHA’ların faaliyet alanlarının genişlemesi, aynı zamanda güvenlik sorunlarını da beraberinde getirmektedir. İHA uçuşları için yasaklanmış olan yerler yasal olarak tanımlanmış olsa da ihlallerin tespitine yönelik tedbirlerin alınması gerekmektedir. Bu çalışmada, ultraviyole görüntüler üzerinde nesnelerin tespit edilmesi için kullanılan ve son zamanlarda önerilen yöntemler test edilmiş ve performansları tartışılmıştır. Modelleri, çeşitli drone görüntülerini toplayarak oluşturduğumuz GDrone isimli yeni bir veri seti üzerinde test ettik. Test edilen YOLOv6 ve YOLOv7 modelleri daha önce bir drone veri seti ile test edilmemiştir. Deneysel testlere göre en başarılı model YOLOv7 mimarisi oldu ve GDrone veri kümesindeki mAP (ortalama hassasiyet) değeri %95,8 olarak belirlendi.

Keywords: İnsansız hava araçları, amatör drone tespiti, evrişimli sinir ağları, İHA veri seti

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APA

Aydın, A., Talan, T., & Aktürk, C. (2023). Vision-Based Amateur Drone Detection: Performance Analysis of New Approaches in Deep Learning. Acta Infologica, 7(2), 308-316. https://doi.org/10.26650/acin.1273088


AMA

Aydın A, Talan T, Aktürk C. Vision-Based Amateur Drone Detection: Performance Analysis of New Approaches in Deep Learning. Acta Infologica. 2023;7(2):308-316. https://doi.org/10.26650/acin.1273088


ABNT

Aydın, A.; Talan, T.; Aktürk, C. Vision-Based Amateur Drone Detection: Performance Analysis of New Approaches in Deep Learning. Acta Infologica, [Publisher Location], v. 7, n. 2, p. 308-316, 2023.


Chicago: Author-Date Style

Aydın, Ahmet, and Tarık Talan and Cemal Aktürk. 2023. “Vision-Based Amateur Drone Detection: Performance Analysis of New Approaches in Deep Learning.” Acta Infologica 7, no. 2: 308-316. https://doi.org/10.26650/acin.1273088


Chicago: Humanities Style

Aydın, Ahmet, and Tarık Talan and Cemal Aktürk. “Vision-Based Amateur Drone Detection: Performance Analysis of New Approaches in Deep Learning.” Acta Infologica 7, no. 2 (May. 2024): 308-316. https://doi.org/10.26650/acin.1273088


Harvard: Australian Style

Aydın, A & Talan, T & Aktürk, C 2023, 'Vision-Based Amateur Drone Detection: Performance Analysis of New Approaches in Deep Learning', Acta Infologica, vol. 7, no. 2, pp. 308-316, viewed 2 May. 2024, https://doi.org/10.26650/acin.1273088


Harvard: Author-Date Style

Aydın, A. and Talan, T. and Aktürk, C. (2023) ‘Vision-Based Amateur Drone Detection: Performance Analysis of New Approaches in Deep Learning’, Acta Infologica, 7(2), pp. 308-316. https://doi.org/10.26650/acin.1273088 (2 May. 2024).


MLA

Aydın, Ahmet, and Tarık Talan and Cemal Aktürk. “Vision-Based Amateur Drone Detection: Performance Analysis of New Approaches in Deep Learning.” Acta Infologica, vol. 7, no. 2, 2023, pp. 308-316. [Database Container], https://doi.org/10.26650/acin.1273088


Vancouver

Aydın A, Talan T, Aktürk C. Vision-Based Amateur Drone Detection: Performance Analysis of New Approaches in Deep Learning. Acta Infologica [Internet]. 2 May. 2024 [cited 2 May. 2024];7(2):308-316. Available from: https://doi.org/10.26650/acin.1273088 doi: 10.26650/acin.1273088


ISNAD

Aydın, Ahmet - Talan, Tarık - Aktürk, Cemal. “Vision-Based Amateur Drone Detection: Performance Analysis of New Approaches in Deep Learning”. Acta Infologica 7/2 (May. 2024): 308-316. https://doi.org/10.26650/acin.1273088



TIMELINE


Submitted29.03.2023
Accepted22.09.2023
Published Online21.11.2023

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