Face recognition based on the proximity measure clustering

Bibliografiske detaljer
Parent link:Компьютерная оптика: научный журнал/ Институт систем обработки изображений Российской академии наук.— , 1987-
Т. 40, № 5.— 2016.— [P. 740-745]
Hovedforfatter: Nemirovskiy V. B. Viktor Borisovich
Institution som forfatter: Национальный исследовательский Томский политехнический университет (ТПУ) Институт социально-гуманитарных технологий (ИСГТ) Кафедра истории и регионоведения (ИСТ)
Andre forfattere: Stoyanov A. K. Aleksandr Kirillovich, Goremykina D. S. Darjya Sergeevna
Summary:Title Screen
In this paper problems of featureless face recognition are considered. The recognition is based on clustering the proximity measures between the distributions of brightness clusters cardinality for segmented images. As a proximity measure three types of distances are used in this work: the Euclidean, cosine and Kullback-Leibler distances. Image segmentation and proximity measure clustering are carried out by means of a software model of the recurrent neural network. Results of the experimental studies of the proposed approach are presented.
Режим доступа: по договору с организацией-держателем ресурса
Sprog:engelsk
Udgivet: 2016
Serier:Image Processing, Pattern Recognition
Fag:
Online adgang:http://elibrary.ru/item.asp?id=27425383
http://earchive.tpu.ru/handle/11683/36151
Format: Electronisk Book Chapter
KOHA link:https://koha.lib.tpu.ru/cgi-bin/koha/opac-detail.pl?biblionumber=652454

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