Application of recurrent neural network for multi-step full-color image segmentation

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

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.

Original language	English
Title of host publication	8th International Forum on Strategic Technology 2013, IFOST 2013 - Proceedings
Pages	221-224
Number of pages	4
Volume	2
DOIs	https://doi.org/10.1109/IFOST.2013.6616891
Publication status	Published - 2013
Event	8th International Forum on Strategic Technology, IFOST 2013 - Ulaanbaatar, Mongolia Duration: 28 Jun 2013 → 1 Jul 2013

Conference

Conference	8th International Forum on Strategic Technology, IFOST 2013
Country	Mongolia
City	Ulaanbaatar
Period	28.6.13 → 1.7.13

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Keywords

clustering
color space
Image
pixel
point map
recurrent neural network
RGB
segmentation
YUV

ASJC Scopus subject areas

Computer Networks and Communications
Software

Cite this

Nemirovskiy, V. B., & Stoyanov, A. K. (2013). Application of recurrent neural network for multi-step full-color image segmentation. In 8th International Forum on Strategic Technology 2013, IFOST 2013 - Proceedings (Vol. 2, pp. 221-224). [6616891] https://doi.org/10.1109/IFOST.2013.6616891

Nemirovskiy, VB & Stoyanov, AK 2013, Application of recurrent neural network for multi-step full-color image segmentation. in 8th International Forum on Strategic Technology 2013, IFOST 2013 - Proceedings. vol. 2, 6616891, pp. 221-224, 8th International Forum on Strategic Technology, IFOST 2013, Ulaanbaatar, Mongolia, 28.6.13. https://doi.org/10.1109/IFOST.2013.6616891

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Access to Document

10.1109/IFOST.2013.6616891