Аpproaches for algorithm selection in semantic image segmentation problem

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dc.contributor.author Kim, A.S.
dc.date.accessioned 2016-06-14T08:20:42Z
dc.date.available 2016-06-14T08:20:42Z
dc.date.issued 2016-06-14
dc.identifier.isbn 978-9965-31-764-4
dc.identifier.uri http://repository.enu.kz:8080/handle/data/12872
dc.description.abstract Semantic image segmentation is a challenging problem in machine vision and mainly consists of two parts: segmenting images into coherent regions and detecting objects inside of those regions. One may think about this problem as finding a way to assign object labels to meaningful parts of an image. For example, figure 1 shows an image for VOC 2012 dataset [1] with its corresponding ground truth image of semantic segmentation. ru_RU
dc.language.iso en ru_RU
dc.relation.ispartofseries UDC;004.93
dc.subject for VOC 2012 ru_RU
dc.subject Algorithm ru_RU
dc.subject Methods and Results ru_RU
dc.title Аpproaches for algorithm selection in semantic image segmentation problem ru_RU
dc.type Article ru_RU


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