Adversarial Learning based framework for Anomaly Detection in the context of Unmanned Aerial Systems
Anomaly detection aims to identify the data samples that do not conform to a known normal (regular) behavior. As the definition of an anomaly is often ambiguous, unsupervised and semi-supervised deep learning (DL) algorithms that primarily use unlabeled datasets to model normal (regular) behaviors,...
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| Format: | Others |
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Virginia Tech
2021
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| Online Access: | http://hdl.handle.net/10919/106935 |