Zobrazeno 1 - 10
of 606
pro vyhledávání: '"drone detection"'
Publikováno v:
Journal of Big Data, Vol 11, Iss 1, Pp 1-15 (2024)
Abstract It is imperative to take a holistic strategy to thwarting drone threats, including the identification of drones and drone-like gadgets like ornithopters that visually imitate birds. In this study, we present the DroneSilient System, a novel
Externí odkaz:
https://doaj.org/article/984802f4a610469687ae9b98f9d2cec8
Publikováno v:
Frontiers in Communications and Networks, Vol 5 (2024)
In recent years, the increasing use of drones for both commercial and recreational purposes has led to heightened concerns regarding airspace safety. To address these issues, machine learning (ML) based drone detection and classification have emerged
Externí odkaz:
https://doaj.org/article/9b1681566ee74456b07b874dabbe01ab
Publikováno v:
IEEE Access, Vol 12, Pp 175458-175471 (2024)
With the rapid advancement of drone technology, there has been a significant increase in the demand for detecting “Low, Slow, and Small” (LSS) drones. However, existing deep learning networks often overlook critical details of such small targets
Externí odkaz:
https://doaj.org/article/8ac354c9d83549f1bb85186153b1d327
Publikováno v:
IEEE Access, Vol 12, Pp 108374-108388 (2024)
Detecting drones is a complex challenge, primarily due to their small feature size for extraction and variable lighting conditions. It is crucial to effectively capture and model features for drone detection. To accurately detect drones, we propose f
Externí odkaz:
https://doaj.org/article/de9a4c12eed148cbb644b1949bfa1e32
Autor:
Fatin Najihah Muhamad Zamri, Teddy Surya Gunawan, Siti Hajar Yusoff, Ahmad A. Alzahrani, Arif Bramantoro, Mira Kartiwi
Publikováno v:
IEEE Access, Vol 12, Pp 90629-90643 (2024)
The increasing misuse of drones poses significant safety and security risks, including illegal transportation of prohibited goods, interference with manned aircraft, and threats to public safety. This has raised concerns about the increased use of un
Externí odkaz:
https://doaj.org/article/f57fc432d6a240288bad7ee5518a7fc2
Autor:
Angelo Coluccia, Alessio Fascista, Lars Sommer, Arne Schumann, Anastasios Dimou, Dimitrios Zarpalas
Publikováno v:
IEEE Open Journal of Signal Processing, Vol 5, Pp 766-779 (2024)
This paper presents the 6th edition of the “Drone-vs-Bird” detection challenge, jointly organized with the WOSDETC workshop within the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) 2023. The main objective of t
Externí odkaz:
https://doaj.org/article/c668ba4d64d54715b62e639cdee0b95c
Publikováno v:
Drones, Vol 8, Iss 11, p 643 (2024)
The frequent illegal use of drones poses a serious threat to public security and property. Counter-drones are crucial tools. The prerequisite for an effective counter-drone is to detect drones accurately. With the rapid advancements in computer visio
Externí odkaz:
https://doaj.org/article/55ab92f332174017afc9a090c4878a24
Autor:
Raj Hakani, Abhishek Rawat
Publikováno v:
Drones, Vol 8, Iss 11, p 680 (2024)
Drones, with their ability to vertically take off and land with their stable hovering performance, are becoming favorable in both civilian and military domains. However, this introduces risks of its misuse, which may include security threats to airpo
Externí odkaz:
https://doaj.org/article/366570fff10040a694efe2fb9a6bdda0
Publikováno v:
Remote Sensing, Vol 16, Iss 22, p 4226 (2024)
In unmanned aerial vehicles (UAVs) detection, challenges such as occlusion, complex backgrounds, motion blur, and inference time often lead to false detections and missed detections. General object detection frameworks encounter difficulties in adequ
Externí odkaz:
https://doaj.org/article/5858f2b44059487c9773e923ffb463ba
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