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- research-articleAugust 2024
Detection of UAVs on a collision course using optical flow
RobCE '24: Proceedings of the 2024 4th International Conference on Robotics and Control EngineeringPages 138–144https://doi.org/10.1145/3674746.3674795This paper presents a method to detect, track and predict a potential collision with UAVs using an aircraft equipped with a single camera. The method analyses the movement in the camera’s image plane by means of sparse optical flow. In this way, the ...
- ArticleAugust 2023
An Improved UAV Detection Method Based on YOLOv5
Advanced Intelligent Computing Technology and ApplicationsPages 739–750https://doi.org/10.1007/978-981-99-4755-3_64AbstractBecause unmanned aerial vehicles(UAVs) have the characteristics of low flight trajectory, slow motion speed, and small volume, they are difficult to identify using current vision technologies. To meet the requirements for detection speed and ...
- research-articleMay 2023
SLBAF-Net: Super-Lightweight bimodal adaptive fusion network for UAV detection in low recognition environment
Multimedia Tools and Applications (MTAA), Volume 82, Issue 30Pages 47773–47792https://doi.org/10.1007/s11042-023-15333-wAbstractUnmanned aerial vehicle (UAV) detection has significant research value in the field of military and civilian applications. However, the traditional object detection algorithms commonly lack satisfying accuracy and robustness due to the intense ...
- research-articleDecember 2022
Robust UAV detection based on saliency cues and magnified features on thermal images
Multimedia Tools and Applications (MTAA), Volume 82, Issue 13Pages 20039–20058https://doi.org/10.1007/s11042-022-14271-3AbstractRecent advances in the development of unmanned aerial vehicles (UAV), also known as drones, raised serious security concerns in critical locations. It is, therefore, necessary to design robust systems that can detect drones in any situation. In ...
- research-articleJanuary 2022
An approach to UAV behaviour classification based on spatial analysis of ADS-B flight data
Procedia Computer Science (PROCS), Volume 201, Issue CPages 338–342https://doi.org/10.1016/j.procs.2022.03.045AbstractProhibited/unauthorized operations of Unmanned Aerial Vehicles (UAV) over civilian aircraft flight space can present safety hazards. We present an approach for classifying UAV flights based on spatial analysis of flight spaces consisting of ...
- research-articleApril 2021
UAVData: A dataset for unmanned aerial vehicle detection
Soft Computing - A Fusion of Foundations, Methodologies and Applications (SOFC), Volume 25, Issue 7Pages 5385–5393https://doi.org/10.1007/s00500-020-05537-9AbstractThe unmanned aerial vehicles (UAVs) significantly contribute to the convenience and intelligence of life. However, the large use of UAVs also leads to high security risk. Only detecting the small and flying UAVs can prevent the safety accidents. ...
- research-articleNovember 2019
RF-based drone detection and identification using deep learning approaches: An initiative towards a large open source drone database
Future Generation Computer Systems (FGCS), Volume 100, Issue CPages 86–97https://doi.org/10.1016/j.future.2019.05.007AbstractThe omnipresence of unmanned aerial vehicles, or drones, among civilians can lead to technical, security, and public safety issues that need to be addressed, regulated and prevented. Security agencies are in continuous search for ...
Highlights- RF-based drone detection is one of the most effective methods for drone detection.
- research-articleDecember 2018
An Unmanned Aerial Vehicle Detection Algorithm Based on Semantic Segmentation and Visual Attention Mechanism
CSAI '18: Proceedings of the 2018 2nd International Conference on Computer Science and Artificial IntelligencePages 309–313https://doi.org/10.1145/3297156.3297269Combined with semantic segmentation and visual attention mechanism, a new method for UAV detection in complex background is presented. The semantic segmentation of target image, which is implemented by Mask R-CNN, is used to exclude invalid regions. ...
- research-articleSeptember 2017
Regularized 2-D complex-log spectral analysis and subspace reliability analysis of micro-Doppler signature for UAV detection
Pattern Recognition (PATT), Volume 69, Issue CPages 225–237https://doi.org/10.1016/j.patcog.2017.04.024The proposed 2-D regularized complex-log-Fourier transform better represents mDS.The proposed subspace reliability analysis better removes unreliable dimensions.The proposed approach demonstrates superior performance for UAV detection. Unmanned aerial ...