Analysis of Application of Cluster Descriptions in Space of Characteristic Image Features

Gorokhovatskyi, V.

Публікація:
Analysis of Application of Cluster Descriptions in Space of Characteristic Image Features

dc.contributor.author	Gorokhovatskyi, V.
dc.date.accessioned	2018-11-15T12:45:49Z
dc.date.available	2018-11-15T12:45:49Z
dc.date.issued	2018
dc.description.abstract	Abstract: Structural image recognition method modifications in space of characteristic features for recognition of computer vision image dataset were investigated. Recognition performance boost is achieved with quantization (clustering) in the space of image characteristic features that form the pattern of the object. Due to the transformation of structural objects descriptions from a set representation to a vector form, the amount of computation might be reduced tens of times. The results of experiments on Leeds Butterfly dataset that confirmed the effectiveness of decision-making systems based on the proposed approach are shown.	uk_UA
dc.identifier.citation	Gorokhovatskyi O. Analysis of Application of Cluster Descriptions in Space of Characteristic Image Features / O. Gorokhovatskyi, V. Gorokhovatskyi, O.Peredrii // Data. – 2018, 3(4), 52. – doi:10.3390/data3040052. Available online: https://www.mdpi.com/2306-5729/3/4/52	uk_UA
dc.identifier.uri	http://openarchive.nure.ua/handle/document/7248
dc.language.iso	en	uk_UA
dc.subject	computer vision	uk_UA
dc.subject	structural recognition methods	uk_UA
dc.subject	set of characteristic features	uk_UA
dc.subject	descriptor	uk_UA
dc.subject	quantization	uk_UA
dc.subject	competitive learning	uk_UA
dc.title	Analysis of Application of Cluster Descriptions in Space of Characteristic Image Features	uk_UA
dc.type	Article	uk_UA
dspace.entity.type	Publication