Multi-Featured Anomaly Detection for Mobile Edge Computing Based UAV Delivery Systems

Xu, L Liu, X Jiang, F

Xu, Y Yao, A Xu, J Li, X

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Field	Value	Language
dc.contributor.author	Xu, L
dc.contributor.author	Liu, X
dc.contributor.author	Jiang, F https://orcid.org/0000-0003-3765-561X
dc.contributor.author	Xu, Y
dc.contributor.author	Yao, A
dc.contributor.author	Xu, J
dc.contributor.author	Li, X
dc.date.accessioned	2024-05-03T00:42:28Z
dc.date.available	2024-05-03T00:42:28Z
dc.date.issued	2023-01-30
dc.identifier.citation	2023 Australasian Computer Science Week, 2023, pp. 58-65
dc.identifier.uri	http://hdl.handle.net/10453/178560
dc.language	en
dc.publisher	Association for Computing Machinery (ACM)
dc.relation.ispartof	2023 Australasian Computer Science Week
dc.relation.ispartof	2023 Australasian Computer Science Week
dc.relation.isbasedon	10.1145/3579375.3579383
dc.rights	info:eu-repo/semantics/closedAccess
dc.title	Multi-Featured Anomaly Detection for Mobile Edge Computing Based UAV Delivery Systems
dc.type	Conference Proceeding
pubs.organisational-group	University of Technology Sydney
pubs.organisational-group	University of Technology Sydney/Faculty of Engineering and Information Technology
utslib.copyright.status	closed_access	*
dc.date.updated	2024-05-03T00:42:25Z
pubs.publication-status	Published

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