Pregled bibliografske jedinice broj: 1196917
Classification of Low-Resolution Flying Objects in Videos Using the Machine Learning Approach
Classification of Low-Resolution Flying Objects in Videos Using the Machine Learning Approach // Advances in Electrical and Computer Engineering, 22 (2022), 2; 45-52 doi:10.4316/AECE.2022.02006 (međunarodna recenzija, članak, znanstveni)
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Naslov
Classification of Low-Resolution Flying Objects
in Videos Using the Machine Learning
Approach
Autori
Stančić, Ivo ; Veić Lucija ; Musić, Josip ; Grujić, Tamara
Izvornik
Advances in Electrical and Computer Engineering (1582-7445) 22
(2022), 2;
45-52
Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni
Ključne riječi
artificial neural networks, computer vision, feature extraction, machine learning, object detection.
Sažetak
A challenge of detecting and identifying drones has emerged due to the significant increase in recreational and commercial drones operating range, payload size, and overall capabilities. Consequently, drones may pose a risk to airspace safety or violate non-flying zone in the vicinity of vulnerable buildings. This paper presents an initial study for a machinelearning classification system applied to flying objects visible with a low resolution that is too distant from the camera to be efficiently classified by other methods. The original dataset in form of labeled high-resolution videos containing lowresolution drone, bird, and airplane objects was collected and carefully prepared. Computationally inexpensive features based on object shape and trajectory descriptors were recommended and tested with several ML models. The accuracy of the best- proposed model tested on our dataset was 98%. The results of this study demonstrate that Machine Learning classification seems to be promising and can be implemented in future multi-stage drone detection and identification system.
Izvorni jezik
Engleski
Znanstvena područja
Elektrotehnika, Računarstvo, Vojno-obrambene i sigurnosno-obavještajne znanosti i umijeće
POVEZANOST RADA
Ustanove:
Fakultet elektrotehnike, strojarstva i brodogradnje, Split
Citiraj ovu publikaciju:
Časopis indeksira:
- Web of Science Core Collection (WoSCC)
- Science Citation Index Expanded (SCI-EXP)
- SCI-EXP, SSCI i/ili A&HCI
- Scopus