Cотрудники института

Ковальчук Андрей Викторович
м.н.с.

Образование:
ННГУ им Лобачевского, 2006, радиофизика, аспирантура Ипф Ран.

Область научных интересов:
Computer vision, machine learning

Количество публикаций:
26

Наиболее значительные работы и результаты:

V. Kovalchuk,  N. S. Bellyustin  “Online learning algorithm of kernel-based ternary classifiers using support vectors” Optical Memory and Neural Networks, July 2013, Volume 22, Issue 3, pp 193-205

An algorithm OnSVM of the kernel-based classification is proposed which solution is very close to -SVM an efficient modification of support vectors machine. The algorithm is faster than batch implementations of -SVM and has a smaller resulting number of support vectors. The approach developed maximizes a margin between a pair of hyperplanes in feature space and can be used in online setup. A ternary classifier of 2-class problem with an “unknown” decision is constructed using these hyperplanes.

(IJACSA) International Journal of Advanced Computer Science and Applications, Special Issue on Artificial Intelligence “Instant Human Face Attributes Recognition System” N.Bellustin, A Kovalchuck, A. Telnykh, O. Shemagina and V.Yakhno, Y. Kalafati,  Abhishek Vaish, Pinki Sharma, Shirshu Verma, 2011 pp 112-120

S.A. Polevaya, A.V. Kovalchuk, S.B.Parin, V.G. Yakhno “Relations between endogenous state of physiological system and conscious perceptions” “International Jpurnal of Psychophysiology” pp. 284-285 ISSN 0167-8760 77(3) 185-342 (2010)

А.В. Ковальчук, М.Е. Соколов, А.А. Тельных. «Нейроноподобная фильтрация в системе распознавания, использующей двухклассовый подход». Сборник научных трудов. Нейроинформатика – 2009. Стр 262 – 270.

M. E. Sokolov, A. A. Tel’nykh, A. V. Koval’chuk, N. S. Bellyustin, I. V. Nuidel’, and V. G. Yakhno, “Face Recognition Using “Lateral Inhibition” Function Features”. Optical Memory and Neural Networks (Information Optics), Vol. 18, No. 1, 2009, pp. 1 – 5

A. V. Kovalchuk, A.A. Telnykh “Object detection system using expert committees”, Pattern Recognition and Image Analysis, Nizhny Novgorod PRIA – 2008 V.1, pp. 343-346