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Recognition Methods in Academician Yu.I. Zhuravlev’s Scientific School

  • SCIENTIFIC SCHOOLS OF THE FEDERAL RESEARCH CENTER “COMPUTER SCIENCE AND CONTROL” OF THE RUSSIAN ACADEMY OF SCIENCES, MOSCOW, THE RUSSIAN FEDERATION
  • Yu.I. Zhuravlev’s Scientific School
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Abstract

This review provides an overview of methods for solving recognition problems developed by the eminent Soviet and Russian academic and scientist, Yu.I. Zhuravlev, together with his students and those that followed him. Zhuravlev was the leader of a prominent scientific school associated with the widespread use of various combinatorial-logical and algebraic methods for in the development of methods for solving recognition tasks. The school’s contributions lie in formulating a universal mathematical lexicon for describing recognition algorithms and an algebraic toolkit tailored for the synthesis of effective algorithms for solving learning problems based on precedents. Within the framework of the scientific school, researchers have devised various recognition methodologies, which have been successfully used to solve numerous applied problems.

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Authors and Affiliations

  1. Federal Research Center “Computer Science and Control” of the Russian Academy of Sciences, 119333, Moscow, Russian Federation

    A. P. Vinogradov, A. A. Dokukin, V. V. Ryazanov & O. V. Senko

  2. Lomonosov Moscow State University, 119991, Moscow, Russian Federation

    A. G. D’yakonov

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  1. A. P. Vinogradov
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  2. A. G. D’yakonov
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  3. A. A. Dokukin
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  4. V. V. Ryazanov
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Correspondence to A. P. Vinogradov, A. G. D’yakonov, A. A. Dokukin, V. V. Ryazanov or O. V. Senko.

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Aleksandr Petrovich Vinogradov. Born in 1951. MSc degree in physics from the Applied Mathematics and Control Department of Moscow Institute of Physics and Technology, 1974. Doctor in mathematical cybernetics, 1978. Senior Researcher at Dorodnicyn Computing Centre, Federal Research Center “Computer Science and Control” of the Russian Academy of Sciences. Author of about 70 scientific papers. Research interests: algebraic and geometrical methods in pattern recognition, image analysis, and processing.

Alexander Gennadjevich D’yakonov. Born in 1979. Doctor of Physical and Mathematical Sciences, Professor of Moscow State University. Multiple winner of international competitions in data science, winner of the first place in the Kaggle ranking of data scientists. Author of three books and more than 80 scientific papers.

Alexander Alexandrovich Dokukin. Born in 1980. Senior researcher at Federal Research Center “Computer Science and Control” of the Russian Academy of Sciences. He graduated with honors from the Faculty of Mathematics and Computer Science at Moscow State University in 2002. In 2005, he completed his postgraduate studies at the same faculty. In 2008, he defended his dissertation for the degree of Candidate of Physical and Mathematical Sciences on the topic “Synthesis of polynomials over extreme algorithms for computing estimates.” Since 2000 he has been working at the Dorodnicyn Research Center of the Russian Academy of Sciences (then the Research Center of the FRC IS RAS). Research interests: pattern recognition and data analysis. He has written and co-authored more than one hundred scientific papers.

Vladimir Vasiljevich Ryazanov. Born in 1950. Graduated from Moscow Institute of Physics and Technology in 1973. He defended his Candidate’s dissertation in 1977 and his Doctoral dissertation in 1994. He has been a full member of the Russian Academy of Natural Sciences since 1998 and a professor since 2008. Since 1976 he has been working at the Computing Center of the Russian Academy of Sciences. Currently, he is the Head of the Department of Data Classification and Analysis Methods at Dorodnicyn Computing Center of the Federal Research Center “Computer Science and Control” of the Russian Academy of Sciences. Author of 208 publications. Research interests: methods of optimization of recognition models, algorithms for searching for and processing logical patterns of classes by precedents, mathematical models of recognition based on voting on sets of logical patterns of classes, committee synthesis of collective clustering and construction of stable solutions in clustering problems, restoration of gaps in data, restoration of regressions on sets of recognition algorithms, creation of software classification systems, and solving practical problems in medicine, technology, chemistry, and other fields.

Oleg Valentinovich Senko. Born in 1957. Graduated from Moscow Institute of Physics and Technology in 1981. In 2007 he defended his dissertation on “Empirical forecasting methods based on stable partitions and collective solutions.” His research interests include methods of machine learning and data mining, as well as their practical applications. Currently he is a leading researcher at the Federal Research Center “Computer Science and Control” of the Russian Academy of Sciences. He is the author of more than 120 scientific articles.

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Vinogradov, A.P., D’yakonov, A.G., Dokukin, A.A. et al. Recognition Methods in Academician Yu.I. Zhuravlev’s Scientific School. Pattern Recognit. Image Anal. 33, 952–982 (2023). https://doi.org/10.1134/S1054661823040521

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