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dc.contributor.authorOsadebey, Michael
dc.contributor.authorPedersen, Marius
dc.contributor.authorWaaler, Dag
dc.date.accessioned2020-03-20T09:54:08Z
dc.date.available2020-03-20T09:54:08Z
dc.date.created2020-02-03T08:04:16Z
dc.date.issued2019
dc.identifier.citationIEEE Conference on Industrial Informatics. 2019, 1211-1216.en_US
dc.identifier.issn1935-4576
dc.identifier.urihttps://hdl.handle.net/11250/2647746
dc.language.isoengen_US
dc.publisherIEEEen_US
dc.titlePlant Leaves Region Segmentation in Cluttered and Occluded Images Using Perceptual Color Space and K-means-Derived Threshold with Set Theoryen_US
dc.typeJournal articleen_US
dc.typePeer revieweden_US
dc.description.versionacceptedVersionen_US
dc.source.pagenumber1211-1216en_US
dc.source.journalIEEE Conference on Industrial Informaticsen_US
dc.identifier.doi10.1109/INDIN41052.2019.8972056
dc.identifier.cristin1789983
dc.description.localcode© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other worksen_US
cristin.unitcode194,63,10,0
cristin.unitcode194,65,70,0
cristin.unitnameInstitutt for datateknologi og informatikk
cristin.unitnameInstitutt for helsevitenskap Gjøvik
cristin.ispublishedtrue
cristin.fulltextpreprint
cristin.qualitycode1


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