A Multifeature Tensor For Remote-Sensing Target Recognition

Zhang, L; Zhang, L; Tao, D; Huang, X

A Multifeature Tensor For Remote-Sensing Target Recognition

Zhang, L Zhang, L Tao, D Huang, X

Publisher:: IEEE-Inst Electrical Electronics Engineers Inc
Publication Type:: Journal Article
Citation:: IEEE Geoscience and Remote Sensing Letters, 2011, 8 (2), pp. 374 - 378
Issue Date:: 2011-01

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Field	Value	Language
dc.contributor.author	Zhang, L	en_US
dc.contributor.author	Zhang, L	en_US
dc.contributor.author	Tao, D	en_US
dc.contributor.author	Huang, X	en_US
dc.date.issued	2011-01	en_US
dc.identifier.citation	IEEE Geoscience and Remote Sensing Letters, 2011, 8 (2), pp. 374 - 378	en_US
dc.identifier.issn	1545-598X	en_US
dc.identifier.uri	http://hdl.handle.net/10453/15374
dc.description.abstract	In remote-sensing image target recognition, the target or background object is usually transformed to a feature vector, such as a spectral feature vector. However, this kind of vector represents only one pixel of a remote-sensing image that considers the	en_US
dc.publisher	IEEE-Inst Electrical Electronics Engineers Inc	en_US
dc.relation.ispartof	IEEE Geoscience and Remote Sensing Letters	en_US
dc.relation.isbasedon	10.1109/LGRS.2010.2077272	en_US
dc.subject.classification	Geological & Geomatics Engineering	en_US
dc.title	A Multifeature Tensor For Remote-Sensing Target Recognition	en_US
dc.type	Journal Article
utslib.citation.volume	2	en_US
utslib.citation.volume	8	en_US
utslib.location.activity	WOS:000287659300039	en_US
utslib.for	0906 Electrical and Electronic Engineering	en_US
utslib.for	0906 Electrical And Electronic Engineering	en_US
utslib.for	0909 Geomatic Engineering	en_US
dc.location.activity	WOS:000287659300039	en_US
pubs.embargo.period	Not known	en_US
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 - AAI - Advanced Analytics Institute Research Centre
pubs.organisational-group	/University of Technology Sydney/Strength - CAI - Centre for Artificial Intelligence
utslib.copyright.status	closed_access
pubs.consider-herdc	true	en_US
pubs.issue	2	en_US
pubs.notes	Ok-SAM	en_US
pubs.volume	8	en_US

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Abstract:

In remote-sensing image target recognition, the target or background object is usually transformed to a feature vector, such as a spectral feature vector. However, this kind of vector represents only one pixel of a remote-sensing image that considers the

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http://hdl.handle.net/10453/15374