论俄罗斯科学院控制科学研究所 20 世纪在模式识别理论和应用领域的工作

IF 0.7 Q4 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS PATTERN RECOGNITION AND IMAGE ANALYSIS Pub Date : 2024-03-20 DOI:10.1134/s1054661823040284

A. S. Mandel, A. I. Mikhalsky

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引用次数: 0

摘要

摘要简要介绍控制科学研究所（IPU RAS）的成立和活动的历史背景。本文介绍了研究所在模式识别和复杂数据相关分析领域的主要研究成果（主要是 20 世纪取得的成果）。它侧重于四个研究领域，包括 (a) 势函数方法，(b) 学习和自学系统理论，(c) 广义肖像方法和基于经验数据的依赖恢复，以及 (d) 自动分类方法和专家分类分析。对这些领域之间的关系进行了研究。该领域的先驱人物有（M.A. Aizerman、E.M. Braverman、L.I. Rozonoer、Ya.Z. Tsypkin、V.N. Vapnik、A.Ya.Chervonenkis, I.B. Muchnik 和 A.A. Dorofeyuk 等），并简要介绍了这些科学家的生平和科研工作。此外，还介绍了这些成果的后续情况。还提供了研究所研究人员在俄罗斯主要期刊上发表的有关模式识别问题和相关复杂数据分析任务的论文目录。

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On the Work of the Institute of Control Sciences of the Russian Academy of Sciences in the Field of Pattern Recognition Theory and Applications in the 20th Century

Abstract

Brief historical background on the establishment and activities of the Institute of Control Sciences (IPU RAS). The paper presents key findings of the Institute (obtained mainly in the 20th century) in the field of pattern recognition and of related analysis of complex data. It focuses on four areas of research including (a) the method of potential functions, (b) the theory of learning and self-learning systems, (c) the generalized portrait method and recovery of dependences based on empirical data, and (d) automatic classification methods and expert classification analysis. Relations between these areas are studied. The pioneers in the field are named (M.A. Aizerman, E.M. Braverman, L.I. Rozonoer, Ya.Z. Tsypkin, V.N. Vapnik, A.Ya. Chervonenkis, I.B. Muchnik, and A.A. Dorofeyuk among others) and brief biographical notes on the life and scientific work of these scientists are presented. The follow-ups of the results thus obtained are shown. The bibliography of publications by the Institute’s researchers in leading journals of Russia on pattern recognition problems and related complex data analysis tasks is provided.

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来源期刊

PATTERN RECOGNITION AND IMAGE ANALYSIS Computer Science-Computer Graphics and Computer-Aided Design

CiteScore

1.80

自引率

20.00%

发文量

期刊介绍： The purpose of the journal is to publish high-quality peer-reviewed scientific and technical materials that present the results of fundamental and applied scientific research in the field of image processing, recognition, analysis and understanding, pattern recognition, artificial intelligence, and related fields of theoretical and applied computer science and applied mathematics. The policy of the journal provides for the rapid publication of original scientific articles, analytical reviews, articles of the world''s leading scientists and specialists on the subject of the journal solicited by the editorial board, special thematic issues, proceedings of the world''s leading scientific conferences and seminars, as well as short reports containing new results of fundamental and applied research in the field of mathematical theory and methodology of image analysis, mathematical theory and methodology of image recognition, and mathematical foundations and methodology of artificial intelligence. The journal also publishes articles on the use of the apparatus and methods of the mathematical theory of image analysis and the mathematical theory of image recognition for the development of new information technologies and their supporting software and algorithmic complexes and systems for solving complex and particularly important applied problems. The main scientific areas are the mathematical theory of image analysis and the mathematical theory of pattern recognition. The journal also embraces the problems of analyzing and evaluating poorly formalized, poorly structured, incomplete, contradictory and noisy information, including artificial intelligence, bioinformatics, medical informatics, data mining, big data analysis, machine vision, data representation and modeling, data and knowledge extraction from images, machine learning, forecasting, machine graphics, databases, knowledge bases, medical and technical diagnostics, neural networks, specialized software, specialized computational architectures for information analysis and evaluation, linguistic, psychological, psychophysical, and physiological aspects of image analysis and pattern recognition, applied problems, and related problems. Articles can be submitted either in English or Russian. The English language is preferable. Pattern Recognition and Image Analysis is a hybrid journal that publishes mostly subscription articles that are free of charge for the authors, but also accepts Open Access articles with article processing charges. The journal is one of the top 10 global periodicals on image analysis and pattern recognition and is the only publication on this topic in the Russian Federation, Central and Eastern Europe.