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电信和无线电工程
SJR: 0.202 SNIP: 0.2 CiteScore™: 0.23

ISSN 打印: 0040-2508
ISSN 在线: 1943-6009

卷:
卷 78, 2019 卷 77, 2018 卷 76, 2017 卷 75, 2016 卷 74, 2015 卷 73, 2014 卷 72, 2013 卷 71, 2012 卷 70, 2011 卷 69, 2010 卷 68, 2009 卷 67, 2008 卷 66, 2007 卷 65, 2006 卷 64, 2005 卷 63, 2005 卷 62, 2004 卷 61, 2004 卷 60, 2003 卷 59, 2003 卷 58, 2002 卷 57, 2002 卷 56, 2001 卷 55, 2001 卷 54, 2000 卷 53, 1999 卷 52, 1998 卷 51, 1997

电信和无线电工程

DOI: 10.1615/TelecomRadEng.v74.i18.60
pages 1671-1683

SELF-LEARNING METHODS IN THE SPACE OF IMAGE STRUCTURAL SIGN CRITERIONS

V. A. Gorokhovatskiy
Kharkiv Educational and Scientific Institute of State Higher Educational Institution (SHEI) "Banking University" Kharkiv, Ukraine
A. Ye. Berestovsky
Kharkiv National University of Radio Engineering and Electronics, 14, Lenin Ave, Kharkiv, 61166, Ukraine
Ye. P. Putyatin
Kharkiv National University of Radio Engineering and Electronics, 14, Lenin Ave, Kharkiv, 61166, Ukraine

ABSTRACT

The issues of enhancing efficiency of the structural image recognition methods in the computer vision systems are discussed. For systematization of the space of signs it is suggested to perform self-learning with application of differential grouping methods and Kohonen networks. As the result, it is developed a more efficient in terms of processing fast-action vector description of the standard bases. The computer modeling results are provided for estimation of the quality of learning and the methods operation capabilities for the application image database.


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