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Online learning with novelty detection in human-guided road tracking

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dc.contributor.authorZhou, Jun
dc.contributor.authorCheng , Li
dc.contributor.authorBischof, Walter F.
dc.date.accessioned2015-12-10T22:15:12Z
dc.date.issued2007
dc.date.updated2015-12-09T08:14:11Z
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.identifier.issn0196-2892
dc.identifier.urihttp://hdl.handle.net/1885/50534
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.bibliographicCitation.issue12
local.bibliographicCitation.lastpage3977
local.bibliographicCitation.startpage3967
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.contributor.authoruidZhou, Jun, u1818501
local.contributor.authoruidCheng , Li, a230209
local.description.embargo2037-12-31
local.description.notesImported from ARIES
local.identifier.absfor080104 - Computer Vision
local.identifier.ariespublicationu8803936xPUB205
local.identifier.citationvolume45
local.identifier.doi10.1109/TGRS.2007.900697
local.identifier.scopusID2-s2.0-36348981725
local.type.statusPublished Version

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