Comparative Analysis of Machine Learning-Based Approaches for Anomaly Detection in Vehicular Data

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datacite.relatedItem.firstPage171
datacite.relatedItem.issue2
datacite.relatedItem.relatedIdentifierTypeISSN
datacite.relatedItem.relatedItemIdentifier2624-8921
datacite.relatedItem.relationTypeIsPublishedIn
datacite.relatedItem.titleVehicles
datacite.relatedItem.volume3
dc.contributor.authorKonstantinos Demestichas
dc.contributor.authorTheodoros Alexakis
dc.contributor.authorNikolaos Peppes
dc.contributor.authorEvgenia Adamopoulou
dc.date.accessioned2025-05-21T03:28:26Z
dc.date.available2025-05-21T03:28:26Z
dc.date.issued2021
dc.identifier.doihttps://doi.org/10.3390/vehicles3020011
dc.identifier.otherjz000163-0011
dc.identifier.urihttps://tustorage.ulb.tu-darmstadt.de/handle/tustorage/33588
dc.publisherMDPI AG
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subject.ddc530
dc.titleComparative Analysis of Machine Learning-Based Approaches for Anomaly Detection in Vehicular Data
dc.typeArticle
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