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Online learning with novelty detection in human-guided road tracking

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Zhou, Jun; Cheng , Li; Bischof, Walter F.

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Current image processing and pattern recognition algorithms are not robust enough to make automated remote sensing image interpretation feasible. For this reason, we need to develop image interpretation systems that rely on human guidance. In this paper,

dc.contributor.authorZhou, Jun
dc.contributor.authorCheng , Li
dc.contributor.authorBischof, Walter F.
dc.date.accessioned2015-12-10T22:15:12Z
dc.identifier.issn0196-2892
dc.identifier.urihttp://hdl.handle.net/1885/50534
dc.description.abstractCurrent image processing and pattern recognition algorithms are not robust enough to make automated remote sensing image interpretation feasible. For this reason, we need to develop image interpretation systems that rely on human guidance. In this paper,
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE Inc)
dc.sourceIEEE Transactions on Geoscience and Remote Sensing
dc.subjectKeywords: E-learning; Feature extraction; Human computer interaction; Iterative methods; Online systems; Aerial images; Image interpretation; Novelty detection; Online learning; Road tracking; Tracking (position) Aerial images; Human-computer interaction (HCI); Image interpretation; Novelty detection; Online learning; Road tracking
dc.titleOnline learning with novelty detection in human-guided road tracking
dc.typeJournal article
local.description.notesImported from ARIES
local.identifier.citationvolume45
dc.date.issued2007
local.identifier.absfor080104 - Computer Vision
local.identifier.ariespublicationu8803936xPUB205
local.type.statusPublished Version
local.contributor.affiliationZhou, Jun, College of Engineering and Computer Science, ANU
local.contributor.affiliationCheng , Li, College of Engineering and Computer Science, ANU
local.contributor.affiliationBischof, Walter F, University of Alberta
local.description.embargo2037-12-31
local.bibliographicCitation.issue12
local.bibliographicCitation.startpage3967
local.bibliographicCitation.lastpage3977
local.identifier.doi10.1109/TGRS.2007.900697
dc.date.updated2015-12-09T08:14:11Z
local.identifier.scopusID2-s2.0-36348981725
CollectionsANU Research Publications

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