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I.G. Persiantsev’s Scientific School at the Lomonosov Moscow State University, Skobeltsyn Institute of Nuclear Physics: History of Development and Overview of Key Works 莫斯科国立罗蒙诺索夫大学斯科别尔琴核物理研究所 I.G. 佩尔相采夫科学院：发展历史和主要成果概述
IF 1
PATTERN RECOGNITION AND IMAGE ANALYSIS Pub Date : 2024-03-20 DOI: 10.1134/s1054661823040132
S. A. Dolenko
{"title":"I.G. Persiantsev’s Scientific School at the Lomonosov Moscow State University, Skobeltsyn Institute of Nuclear Physics: History of Development and Overview of Key Works","authors":"S. A. Dolenko","doi":"10.1134/s1054661823040132","DOIUrl":"https://doi.org/10.1134/s1054661823040132","url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Abstract</h3><p>This article is devoted to the history of development and main research areas of the scientific school in the field of pattern recognition, image processing and analysis, and artificial intelligence and machine learning, founded in the early 1990s at the Skobeltsyn Institute of Nuclear Physics, Lomonosov Moscow State University (SINP MSU) by Prof. Igor’ Georgievich Persiantsev. For many years Persiantsev was the permanent leader of this scientific school; he laid down the basic principles and approaches to scientific research that still guide his disciples to this day. During this time, more than 30 people became students of Persiantsev’s school, who carried out scientific work under his leadership or under the leadership of his disciples, defended their candidate’s dissertations or diploma at the Faculty of Physics, Lomonosov Moscow State University. The article provides a brief historical background and an overview of the areas of research and major works published over more than 30 years (from 1992 to 2023) by Persiantsev and his disciples.</p>","PeriodicalId":35400,"journal":{"name":"PATTERN RECOGNITION AND IMAGE ANALYSIS","volume":"22 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2024-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140884994","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Earth Remote Sensing and Geographic Information Systems 地球遥感和地理信息系统
IF 1
PATTERN RECOGNITION AND IMAGE ANALYSIS Pub Date : 2024-03-20 DOI: 10.1134/s1054661823040454
V. A. Soifer, V. V. Sergeev, V. N. Kopenkov, A. V. Chernov
{"title":"Earth Remote Sensing and Geographic Information Systems","authors":"V. A. Soifer, V. V. Sergeev, V. N. Kopenkov, A. V. Chernov","doi":"10.1134/s1054661823040454","DOIUrl":"https://doi.org/10.1134/s1054661823040454","url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Abstract</h3><p>The article examines the role and place of Earth remote sensing (ERS) in geographic information systems. The stages of development of remote sensing and geoinformatics are given, as well as a brief overview of Russian means of obtaining, receiving, and processing satellite images. The specifics and tasks of processing remote sensing data, including hyperspectral data, as well as the experience of using remote sensing data and geoinformation to solve practical problems of managing the territory of the Samara oblast are considered.</p>","PeriodicalId":35400,"journal":{"name":"PATTERN RECOGNITION AND IMAGE ANALYSIS","volume":"13 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2024-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140885027","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Optimization in Automation Systems for Design and Management: Scientific and Pedagogical School of Dmitry Ivanovich Batishchev 自动化系统的优化设计与管理》：德米特里-伊万诺维奇-巴蒂什切夫科学与师范学校
IF 1
PATTERN RECOGNITION AND IMAGE ANALYSIS Pub Date : 2024-03-20 DOI: 10.1134/s1054661823040041
L. G. Afraimovich, P. D. Basalin, A. G. Korotchenko, M. Kh. Prilutskii, N. V. Starostin
{"title":"Optimization in Automation Systems for Design and Management: Scientific and Pedagogical School of Dmitry Ivanovich Batishchev","authors":"L. G. Afraimovich, P. D. Basalin, A. G. Korotchenko, M. Kh. Prilutskii, N. V. Starostin","doi":"10.1134/s1054661823040041","DOIUrl":"https://doi.org/10.1134/s1054661823040041","url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Abstract</h3><p>Information about the Nizhny Novgorod scientific and pedagogical school Optimization in Automation Systems for Design and Control is presented. The founder of the school is Honored Scientist of the Russian Federation, Professor Dmitrii Ivanovich Batishchev.</p>","PeriodicalId":35400,"journal":{"name":"PATTERN RECOGNITION AND IMAGE ANALYSIS","volume":"17 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2024-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140885028","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Ural School of Pattern Recognition: Majoritarian Approach to Ensemble Learning 乌拉尔模式识别学院：集合学习的多数派方法
IF 1
PATTERN RECOGNITION AND IMAGE ANALYSIS Pub Date : 2024-03-20 DOI: 10.1134/s1054661823040314
Vl. D. Mazurov, M. I. Poberii, M. Yu. Khachai
{"title":"Ural School of Pattern Recognition: Majoritarian Approach to Ensemble Learning","authors":"Vl. D. Mazurov, M. I. Poberii, M. Yu. Khachai","doi":"10.1134/s1054661823040314","DOIUrl":"https://doi.org/10.1134/s1054661823040314","url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Abstract</h3><p>This article provides an overview of the significant achievements of the Ural School of Pattern Recognition. The focus is on majoritarian generalized solutions for algebraic equations and inequalities that may not always adhere to standard properties. The paper also delves into the broader applications of these findings in collective machine learning techniques. In the literature, these generalized solutions are frequently referred to as committee generalized solutions or simply committees, leading to the derived learning methods being called committee machines. Our discussion primarily centers on the foundational theorems confirming the existence of such solutions, the intricacies of combinatorial optimization during their exploration, and the subsequent emergence of collective machine learning algorithms.</p>","PeriodicalId":35400,"journal":{"name":"PATTERN RECOGNITION AND IMAGE ANALYSIS","volume":"109 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2024-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140884956","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Systems for Recognition and Intelligent Analysis of Biomedical Images 生物医学图像识别和智能分析系统
IF 1
PATTERN RECOGNITION AND IMAGE ANALYSIS Pub Date : 2024-03-20 DOI: 10.1134/s105466182304020x
N. Yu. Ilyasova, N. S. Demin
{"title":"Systems for Recognition and Intelligent Analysis of Biomedical Images","authors":"N. Yu. Ilyasova, N. S. Demin","doi":"10.1134/s105466182304020x","DOIUrl":"https://doi.org/10.1134/s105466182304020x","url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Abstract</h3><p>The article is devoted to the achievements of the leading scientific school of Academician V.A. Soifer in the field of biomedical image processing. The main stages of development of research in the field of analysis of medical data are given. Various tasks in processing, analysis, and recognition of medical images, as well as their specifics, are considered. Methods, algorithms, and systems obtained during joint research with major medical institutions in the Russian Federation are described.</p>","PeriodicalId":35400,"journal":{"name":"PATTERN RECOGNITION AND IMAGE ANALYSIS","volume":"230 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2024-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140205490","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Analysis and Classification of Biomedical and Bioinformation Systems Using a Generalized Spectral Analytical Approach 使用广义光谱分析方法对生物医学和生物信息系统进行分析和分类
IF 1
PATTERN RECOGNITION AND IMAGE ANALYSIS Pub Date : 2024-03-20 DOI: 10.1134/s1054661823040259
L. I. Kulikova, S. A. Makhortykh
{"title":"Analysis and Classification of Biomedical and Bioinformation Systems Using a Generalized Spectral Analytical Approach","authors":"L. I. Kulikova, S. A. Makhortykh","doi":"10.1134/s1054661823040259","DOIUrl":"https://doi.org/10.1134/s1054661823040259","url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Abstract</h3><p>A generalized spectral analytical method is outlined—a new approach to processing information arrays. The theoretical foundations of the method are presented, as well as its applications to various problems of processing of experimental data and problems of analysis, recognition, and diagnostics of biomedical and bioinformation systems. Examples of its use for studying biomagnetic data and structures of biomacromolecules are given. The problems of its application for image analysis and recognition are formulated. The method is based on the adaptive decomposition of the original arrays in a functional basis from among classical algebraic systems of polynomials and functions (Jacobi, Chebyshev, Lagrange, Laguerre, and Gegenbauer polynomials, etc., having one and two variables), as well as spherical functions. This approach combines analytical and digital data-processing procedures and is in fact a universal combined technology for processing information arrays.</p>","PeriodicalId":35400,"journal":{"name":"PATTERN RECOGNITION AND IMAGE ANALYSIS","volume":"20 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2024-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140884957","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Magnetometric SQUID Systems and Magnetic Measurement Methods for Biomedical Research 用于生物医学研究的磁测量 SQUID 系统和磁测量方法
IF 1
PATTERN RECOGNITION AND IMAGE ANALYSIS Pub Date : 2024-03-20 DOI: 10.1134/s1054661823040296
Yu. V. Maslennikov, V. Yu. Slobodchikov, V. A. Krymov, Yu. V. Gulyaev
{"title":"Magnetometric SQUID Systems and Magnetic Measurement Methods for Biomedical Research","authors":"Yu. V. Maslennikov, V. Yu. Slobodchikov, V. A. Krymov, Yu. V. Gulyaev","doi":"10.1134/s1054661823040296","DOIUrl":"https://doi.org/10.1134/s1054661823040296","url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Abstract</h3><p>This article presents a review of domestic research on the development of new medical equipment and technologies using equipment and methods of detection of natural magnetic fields of biological objects. The core of the biomagnetic research technology consists of noncontact detection, special mathematical processing, and analysis of the values of the parameters of the magnetic field of the investigated bioobject (generated by the heart, brain, muscles, etc.) found in the specified points of space outside the body of the bioobject using highly sensitive magnetometer equipment, and in particular, using superconducting quantum interference devices (SQUIDs). Based on the studies of myocardial electrophysiology, the samples of technical solutions of magnetometric SQUID-systems for magnetocardiography (MCG), data on diagnostic capabilities, and prospects of practical application of MCG in cardiology are presented. The methodology of magnetocardiographic examination is described and the advantages of MCG application for early diagnosis and control of therapy of various cardiovascular diseases (CVDs) are described. The work of the software of MAG-SCAN diagnostic complexes for the analysis of magnetocardiosignals is illustrated by solving the problem of classifying groups of cardiological patients.</p>","PeriodicalId":35400,"journal":{"name":"PATTERN RECOGNITION AND IMAGE ANALYSIS","volume":"284 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2024-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140885025","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Image Analysis and Enhancement: General Methods and Biomedical Applications 图像分析与增强：一般方法和生物医学应用
IF 1
PATTERN RECOGNITION AND IMAGE ANALYSIS Pub Date : 2024-03-20 DOI: 10.1134/s1054661823040235
A. S. Krylov, A. V. Nasonov, D. V. Sorokin, A. V. Khvostikov, E. A. Pavelyeva, Ya. A. Pchelintsev
{"title":"Image Analysis and Enhancement: General Methods and Biomedical Applications","authors":"A. S. Krylov, A. V. Nasonov, D. V. Sorokin, A. V. Khvostikov, E. A. Pavelyeva, Ya. A. Pchelintsev","doi":"10.1134/s1054661823040235","DOIUrl":"https://doi.org/10.1134/s1054661823040235","url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Abstract</h3><p>General methods of image processing, analysis and enhancement and their biomedical applications developed by the scientific school of the Laboratory of Mathematical Methods of Image Processing of the Faculty of Computational Mathematics and Cybernetics of Lomonosov Moscow State University are reviewed. The suggested general methods and algorithms of image quality enhancement for image resampling and super-resolution, ringing artifact reduction, image sharpening, image denoising, and image registration are described. Image analysis methods based on Hermite projection method, Gauss-Laguerre functions and the use of phase information are presented. We describe and review the developed methods for medical imaging tasks solution, including problems in histology, color Doppler flow mapping, ultrasound liver fibrosis diagnostics, CT brain perfusion, Alzheimer’s disease diagnostics, dermatology, chest X-ray image analysis, live cell image registration, tracking, segmentation and synthesis. The paper illustrates the basic research idea of the effectiveness of the hybrid approach when we jointly use classical mathematical methods and deep learning approaches.</p>","PeriodicalId":35400,"journal":{"name":"PATTERN RECOGNITION AND IMAGE ANALYSIS","volume":"16 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2024-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140885119","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
The Possibilities of Diagnosis and Prediction of Cardiac Disorders Based on the Results of Mathematical Modeling of the Myocardium and Regulation of Action of the Heart 根据心肌数学建模和心脏作用调节的结果诊断和预测心脏疾病的可能性
IF 1
PATTERN RECOGNITION AND IMAGE ANALYSIS Pub Date : 2024-03-20 DOI: 10.1134/s1054661823040272
S. A. Makhortykh, A. V. Moskalenko
{"title":"The Possibilities of Diagnosis and Prediction of Cardiac Disorders Based on the Results of Mathematical Modeling of the Myocardium and Regulation of Action of the Heart","authors":"S. A. Makhortykh, A. V. Moskalenko","doi":"10.1134/s1054661823040272","DOIUrl":"https://doi.org/10.1134/s1054661823040272","url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Abstract</h3><p>Theoretical approaches to solving problems of diagnosing and predicting cardiac dysfunctions within the framework of modern mathematical physics of the heart (cardiophysics) are presented. The possibilities for diagnostic purposes of using recognition of patterns of behavior of autowave vortices that arise in the heart during dangerous disturbances in its functioning are considered. The prospects for the development of new methods for diagnosing patterns of the basic heart rhythm in the development of already recognized methods for analyzing heart rate variability are discussed.</p>","PeriodicalId":35400,"journal":{"name":"PATTERN RECOGNITION AND IMAGE ANALYSIS","volume":"62 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2024-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140885123","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Research Overview on Statistical Image Analysis Conducted at Ulyanovsk State Technical University 乌里扬诺夫斯克国立技术大学开展的图像统计分析研究概述
IF 1
PATTERN RECOGNITION AND IMAGE ANALYSIS Pub Date : 2024-03-20 DOI: 10.1134/s1054661823040508
K. K. Vasilyev, V. R. Krasheninnikov, A. G. Tashlinskii
{"title":"Research Overview on Statistical Image Analysis Conducted at Ulyanovsk State Technical University","authors":"K. K. Vasilyev, V. R. Krasheninnikov, A. G. Tashlinskii","doi":"10.1134/s1054661823040508","DOIUrl":"https://doi.org/10.1134/s1054661823040508","url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Abstract</h3><p>This paper presents a series of research findings on methods for representation, filtering, parameter estimation (including geometric deformation parameters), detection, and recognition of multidimensional images and their sequences, conducted over 40 years at the scientific school of Ulyanovsk State Technical University, founded by Professor Konstantin Konstantinovich Vasilyev.</p>","PeriodicalId":35400,"journal":{"name":"PATTERN RECOGNITION AND IMAGE ANALYSIS","volume":"6 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2024-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140201467","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
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