Аpproaches for algorithm selection in semantic image  segmentation problem

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