Semantic segmentation by ways of interactive post-processing with active contours model

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dc.contributor.authorKubigenov, Darkhan
dc.date.accessioned2018-10-31T04:33:54Z
dc.date.available2018-10-31T04:33:54Z
dc.date.issued2017-04
dc.description.abstractActive contour has been proven to be effective at solving semantic segmentation of images. However, the use cases of such approaches were mostly on trivial problems with narrow utility. For instance, it was used for detecting tumors from MRI scans and finding oil spills from aerial photographs. This thesis considers ways of making active contour work for any kinds of images. Active contour is applied at post-processing step on results from other algorithms.en_US
dc.identifier.citationDarkhan Kubigenov. Semantic segmentation by ways of interactive post-processing with active contours model. 2017. Department of Computer Science, School of Science and Technology, Nazarbayev Universityen_US
dc.identifier.urihttp://nur.nu.edu.kz/handle/123456789/3568
dc.language.isoenen_US
dc.publisherNazarbayev University School of Science and Technologyen_US
dc.rightsAttribution-NonCommercial-ShareAlike 3.0 United States*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/3.0/us/*
dc.subjectimagesen_US
dc.titleSemantic segmentation by ways of interactive post-processing with active contours modelen_US
dc.typeMaster's thesisen_US
workflow.import.sourcescience

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