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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Hlavní autoři:	Milad Memarzadeh, Ata Akbari Asanjan, Bryan Matthews
Médium:	Artigo
Jazyk:	Inglês
Vydáno:	MDPI AG 2022-08-01
Edice:	Aerospace
Témata:	anomaly detection semi-supervised learning explainable AI aviation safety
On-line přístup:	https://www.mdpi.com/2226-4310/9/8/437
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