Robust and Explainable Semi-Supervised Deep Learning Model for Anomaly Detection in Aviation
Identifying safety anomalies and vulnerabilities in the aviation domain is a very expensive and time-consuming task. Currently, it is accomplished via manual forensic reviews by subject matter experts (SMEs). However, with the increase in the amount of data produced in airspace operations, relying o...
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| Principais autores: | , , |
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| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
MDPI AG
2022-08-01
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| coleção: | Aerospace |
| Assuntos: | |
| Acesso em linha: | https://www.mdpi.com/2226-4310/9/8/437 |
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