Face recognition based on the proximity measure clustering; Компьютерная оптика; Т. 40, № 5

Dettagli Bibliografici
Parent link:Компьютерная оптика: научный журнал/ Институт систем обработки изображений Российской академии наук.— , 1987-
Т. 40, № 5.— 2016.— [P. 740-745]
Autore principale: Nemirovskiy V. B. Viktor Borisovich
Ente Autore: Национальный исследовательский Томский политехнический университет (ТПУ) Институт социально-гуманитарных технологий (ИСГТ) Кафедра истории и регионоведения (ИСТ)
Altri autori: Stoyanov A. K. Aleksandr Kirillovich, Goremykina D. S. Darjya Sergeevna
Riassunto: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
Lingua:inglese
Pubblicazione: 2016
Serie:Image Processing, Pattern Recognition
Soggetti:
Accesso online:http://elibrary.ru/item.asp?id=27425383
http://earchive.tpu.ru/handle/11683/36151
Natura: MixedMaterials Elettronico Capitolo di libro
KOHA link:https://koha.lib.tpu.ru/cgi-bin/koha/opac-detail.pl?biblionumber=652454

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