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Telecommunication Systems

RF-YOLO: a modified YOLO model for UAV detection and classification using RF spectrogram images

  • 01-03-2025
Published in:
Authors
Tijeni Delleji
Feten Slimeni
Published in
Telecommunication Systems | Issue 1/2025

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Abstract

The article introduces RF-YOLO, a modified YOLO model designed for UAV detection and classification using RF spectrogram images. This model addresses the challenges of traditional detection methods such as radar, optical, and acoustic systems by leveraging RF signals. RF-YOLO is optimized with a wider backbone and a SinLU activation function to capture fine-grained patterns in high-resolution spectrogram images, achieving superior accuracy and robustness. The model excels in non-line-of-sight and noisy environments, making it a practical solution for critical applications like air traffic management and counter-drone operations. The article highlights the performance of RF-YOLO through extensive experiments and comparisons with other state-of-the-art models, demonstrating its potential to enhance air safety and security.
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previous article Performance evaluation of RIS mounted UAV communication system with RF energy harvesting
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Title
RF-YOLO: a modified YOLO model for UAV detection and classification using RF spectrogram images
Authors
Tijeni Delleji
Feten Slimeni
Publication date
01-03-2025
Publisher
Springer US
Published in
Telecommunication Systems / Issue 1/2025
Print ISSN: 1018-4864
Electronic ISSN: 1572-9451
DOI
https://doi.org/10.1007/s11235-025-01264-4
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