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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| Autors principals: | , |
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| Format: | Artigo |
| Idioma: | Inglês |
| Publicat: |
SpringerOpen
2026-01-01
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| Col·lecció: | Cybersecurity |
| Matèries: | |
| Accés en línia: | https://doi.org/10.1186/s42400-025-00422-0 |
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