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Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/99865
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dc.contributor.authorZhao, Y.-
dc.contributor.authorLi, W.-
dc.contributor.authorShi, P.-
dc.date.issued2016-
dc.identifier.citationNeurocomputing, 2016; 182:255-266-
dc.identifier.issn0925-2312-
dc.identifier.issn1872-8286-
dc.identifier.urihttp://hdl.handle.net/2440/99865-
dc.description.abstractAbstract not available-
dc.description.statementofresponsibilityYuxin Zhao, Wang Li, Peng Shi-
dc.language.isoen-
dc.publisherElsevier-
dc.rightsCrown Copyright © 2015 Published by Elsevier B.V. All rights reserved.-
dc.source.urihttp://dx.doi.org/10.1016/j.neucom.2015.12.028-
dc.titleA real-time collision avoidance learning system for Unmanned Surface Vessels-
dc.typeJournal article-
dc.identifier.doi10.1016/j.neucom.2015.12.028-
dc.relation.granthttp://purl.org/au-research/grants/arc/DP140102180-
dc.relation.granthttp://purl.org/au-research/grants/arc/LP140100471-
dc.relation.granthttp://purl.org/au-research/grants/arc/LE150100079-
pubs.publication-statusPublished-
dc.identifier.orcidShi, P. [0000-0001-8218-586X]-
Appears in Collections:Aurora harvest 3
Electrical and Electronic Engineering publications

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