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Fined-grained unmanned aerial vehicle anomaly detection by fusing multi-domain features

Abstract Unmanned aerial vehicle (UAV) fault brings about anomalies of sensors data, which can have serious and catastrophic consequences. Therefore, UAV anomaly detection (UAVAD) is crucial for its safe flight. As fail to differentiate the fined-grained feature error and fuse multi-domain features,...

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Bibliografski detalji
Glavni autori: Jiajia Zhou, Yian Zhu
Format: Artigo
Jezik:Inglês
Izdano: SpringerOpen 2026-01-01
Serija:Cybersecurity
Teme:
Online pristup:https://doi.org/10.1186/s42400-025-00422-0
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