Application of recurrent neural network for multi-step full-color image segmentation; The 8th International Forum on Strategic Technology (IFOST-2013), June 28 - July 1, 2013, Ulaanbaatar, Mongolia; Vol. 2

Application of recurrent neural network for multi-step full-color image segmentation; The 8th International Forum on Strategic Technology (IFOST-2013), June 28 - July 1, 2013, Ulaanbaatar, Mongolia; Vol. 2

Bibliographische Detailangaben
Parent link:The 8th International Forum on Strategic Technology (IFOST-2013), June 28 - July 1, 2013, Ulaanbaatar, Mongolia: [proceedings]/ Mongolian University of Science and Technology.— , 2013
Vol. 2.— 2013.— [P. 221-224]
1. Verfasser: Nemirovskiy V. B. Viktor Borisovich
Körperschaft: Национальный исследовательский Томский политехнический университет (ТПУ) Институт кибернетики (ИК) Кафедра информатики и проектирования систем (ИПС)
Weitere Verfasser: Stoyanov A. K. Aleksandr Kirillovich
Zusammenfassung:Title screen
Possibility of application of a recurrent neural network for segmentation of full-color images based on a clustering of color components is considered. Questions of multi-step segmentation of such images in different color models are discussed. Experimental results on multi-step segmentation of images are presented in the RGB and YUV color spaces.
[References: 6 tit.]
Режим доступа: по договору с организацией-держателем ресурса
Sprache:Englisch
Veröffentlicht: 2013
Schlagworte:
труды учёных ТПУ
электронный ресурс
критические точки
изображения
пиксели
Online-Zugang:http://dx.doi.org/10.1109/IFOST.2013.6616891
Format: Elektronisch Buchkapitel
KOHA link:https://koha.lib.tpu.ru/cgi-bin/koha/opac-detail.pl?biblionumber=645353

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