Combining HWEBING and HOG‐MLBP features for pedestrian detection

Xiao, L Zhang, Y Zhang, J

Wang, Q Li, Y

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Field	Value	Language
dc.contributor.author	Xiao, L
dc.contributor.author	Zhang, Y
dc.contributor.author	Zhang, J https://orcid.org/0000-0002-7240-3541
dc.contributor.author	Wang, Q
dc.contributor.author	Li, Y
dc.date.accessioned	2022-08-24T03:59:26Z
dc.date.available	2022-08-24T03:59:26Z
dc.date.issued	2018-09-25
dc.identifier.citation	The Journal of Engineering, 2018, 2018, (16), pp. 1421-1426
dc.identifier.issn	2314-4904
dc.identifier.issn	2051-3305
dc.identifier.uri	http://hdl.handle.net/10453/160771
dc.language	en
dc.publisher	Institution of Engineering and Technology (IET)
dc.relation.ispartof	The Journal of Engineering
dc.relation.isbasedon	10.1049/joe.2018.8308
dc.rights	info:eu-repo/semantics/openAccess
dc.subject	09 Engineering
dc.title	Combining HWEBING and HOG‐MLBP features for pedestrian detection
dc.type	Journal Article
utslib.citation.volume	2018
utslib.for	09 Engineering
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Strength - GBDTC - Global Big Data Technologies
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Electrical and Data Engineering
utslib.copyright.status	open_access	*
dc.date.updated	2022-08-24T03:59:25Z
pubs.issue	16
pubs.publication-status	Published
pubs.volume	2018
utslib.citation.issue	16

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