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Аналитический обзор методов извлечения текстовых транскрипций из речевых высказываний
С. 336–340.
Ролинский С. О., Dvoynikova A.
Lebedev O. B., Шмелева А. Г., Гежа Н. С., Информатика и автоматизация (Труды СПИИРАН) 2026 Т. 25 № 3 С. 720–750
This paper describes the development of a neural network model for automated analysis of medical data in electrophysiology based on deep learning methods. The relevance of this work stems from the growing need to improve the objectivity, speed, and accuracy of processing complex spatiotemporal signals, such as ECG or EEG. Convolutional neural networks (CNNs), which ...
Added: September 10, 2026
Неверов В. Д., Красавин А. В., Vagov A. et al., Physical Review B: Condensed Matter and Materials Physics 2026 Vol. 113 P. 1–6
We develop a neural network approach to solve the self-consistent Bogoliubov-de Gennes equations in strongly disordered s-wave superconductors. The method accurately reproduces inhomogeneous gap distributions and generalizes to system sizes far larger than those used in training. It reduces computational scaling from O(N6 ) to O(N2), enabling quantitative analysis of percolation phenomena and the superconductor-insulator ...
Added: September 5, 2026
Khodadoust J., Kulikova S., Khodadoust F., Biomedical Signal Processing and Control 2027 Vol. 129 P. 111284–111284
Acute ischemic stroke (AIS) analysis from two-dimensional (2D) clinical imaging is hindered by uncontrolled slice tilt and geometric inconsistencies that violate the assumptions of pose-agnostic deep learning (DL) models. This paper proposes a unified geometry-aware, frequency-domain framework for tilted slice localization and ischemic stroke segmentation that explicitly decouples pose estimation from lesion analysis. The method ...
Added: September 2, 2026
Seul: PMLR, 2026.
Added: June 4, 2026
Chertopolokhov V., Mukhamedov A., Bugriy G. et al., IEEE Access 2026 Vol. 14 P. 14369–14392
This study presents on-the-fly identification and multi-step prediction of nonlinear systems with delayed inputs using a dynamic neural network combined with a smooth projection onto ellipsoids. The projection enforces parameter constraints that guarantee stability, while a Lyapunov–Krasovskii analysis yields computable ultimate error bounds. Riccati-type matrix inequalities are derived, providing an efficient vectorization–projection–devectorization implementation suitable for ...
Added: May 22, 2026
Dvoynikova A., Садикова А. А., В кн.: Сборник трудов X Конгресса молодых ученыхТ. 1.: Университет ИТМО, 2021.
В работе рассматривается применение различных планировщиков обучения (англ. scheduler) нейронных сетей для задачи текстонезависимой верификации дикторов. Для экспериментальных исследований использовалась база данных VoxCeleb1, которая содержит в себе различные речевые высказывания 1211 дикторов. В работе проводился анализ влияния различных планировщиков обучения нейронных сетей, представленных в библиотеке PyTorch языка программирования Python, а также 2 алгоритма планировщика, представленных ...
Added: April 24, 2026
Dvoynikova A., Верхоляк О. В., Карпов А. А., В кн.: Альманах научных работ молодых ученых Университета ИТМОТ. 3.: Университет ИТМО, 2020.
В работе предлагается метод, основанный на тональных словарях, для анализа тональности разговорной речи. Для проведения экспериментов используются транскрипции аудиозаписей базы данных RAMAS, полученные с помощью систем автоматического распознавания речи. Машинная классификация данных производится на 3 класса: позитивный, нейтральный и негативный с использованием русскоязычных тональных словарей RuSentiLex, LinisCrowd, WordNetAffect и словаря Белякова. ...
Added: April 24, 2026
Efremov A., Portnoy S., Волошин А. Д., Первая миля 2025 № 8 С. 20–28
Выполнен комплексный обзор методов машинного обучения (ML), применяемых для повышения устойчивости сигнала к помехам в каналах связи. Бурное развитие поколений беспроводной связи, активная разработка концепции 6G предъявляют высокие требования к задержке, скорости и надежности передачи данных. Традиционные подходы к защите от помех, основанные на строгих аналитических моделях, зачастую не справляются с хаотичной природой плотных гетерогенных ...
Added: April 4, 2026
Пермь: Пермский государственный национальный исследовательский университет, 2024.
This collection presents the proceedings of the Ninth All-Russian Scientific and Practical Conference with International Participation, "Artificial Intelligence in Solving Current Social and Economic Problems of the 21st Century," which was held October 17–18, 2024, in Perm. The collection is intended for researchers and educators, lecturers, postgraduate and master's students, undergraduates, and anyone interested in ...
Added: November 19, 2025
Penskaja E., Имагология и компаративистика 2025 № 23 С. 380–389
The book Artificial Intelligence, Archives and Manuscripts. New Relationships between the Virtual Archive and Its Referent (2025) is presented. This collective monograph discusses both technological and legal, intellectual issues that researchers and archivists face in automated work with manuscript heritage, artificial intelligence and neural networks. ...
Added: October 30, 2025
Surkov A., Sergei Koltcov, Ignatenko V. et al., Physica A: Statistical Mechanics and its Applications 2025 Vol. 681 Article 131085
Neural networks are powerful tools capable of achieving state-of-the-art performance across a wide range of tasks; however, their effectiveness often comes at the cost of extremely large numbers of parameters, which can hinder their deployment in resource-constrained environments. To address this issue, various pruning techniques have been proposed to reduce model size and complexity while ...
Added: October 30, 2025
Dogonasheva O., Doelling K., Zakharov D. et al., Nature Computational Science 2025 Vol. 5 P. 915–926
Unraveling how humans understand speech despite distortions has long intrigued researchers. A prominent hypothesis highlights the role of multiple endogenous brain rhythms in forming the computational context to predict speech structure and content. Yet, how neural processes may implement rhythm-based context formation remains unclear. Here, we propose the Brain-Rhythm-Based Inference model (BRyBI) as a possible neural implementation of speech processing ...
Added: September 2, 2025
Рожин А. К., Бабинцев Л. В., Nefedov S. et al., Наноиндустрия 2024 Т. 17 № S10-2(128) С. 752–755
Распространение систем искусственного интеллекта ведет к повышенному спросу на вычислительные ресурсы, импорт которых стал затруднен. В статье приводится результат исследования отечественной элементной базы, разработан аппаратно-программный комплекс на ее основе. Протестирована скорость вывода и эффективность адаптированных современных нейросетевых алгоритмов. ...
Added: June 20, 2025
Boltunova E., Laptev A., Имагология и компаративистика 2025 № 23 С. 358–379
Added: June 16, 2025
Pshichenko D., Тенденции развития науки и образования 2024 № 112(3) С. 117–122
The article examines the role of artificial intelligence (AI) in managing crisis situations in the economy. Various AI technologies for forecasting economic shocks and minimizing their consequences are analyzed. Examples of successful AI applications in various sectors are studied. It is emphasized that the use of AI significantly enhances the resilience and adaptability of economic ...
Added: March 10, 2025
Курск: Курский государственный университет, 2024.
The collection publishes scientific articles based on the materials of the V International Scientific and Technical Conference "Intelligent Information Systems: Theory and Practice". The publication is addressed to students, postgraduates, university professors, candidates and doctors of science, practicing specialists, and anyone interested in the design and development of intelligent information systems, their practical applications, as ...
Added: February 17, 2025
Derkach D., Hushchyn M., Samorodova E. et al., Astronomical Society of the Pacific: Conference Series 2024 Vol. 535
In this study, we apply shallow neural networks, bayesian neural networks, and normalizing flows to approximate light curves of astronomical objects. The study shows that the approximation quality of the proposed methods outperform the existing ap- proaches based on Gaussian processes. We assess the quality of solution using two physics-motivated analyses: supernovae type Ia classification ...
Added: January 8, 2025
Fedorova A., Jovišić N., Vallverdù J. et al., Advanced Electronic Materials 2024 Vol. 10 No. 12 Article 2400258
The energy efficiency of Artificial Intelligence (AI) systems is a crucial and actual issue that may have an important impact on an ecological, economic and technological level. Spiking Neural Networks (SNNs) are strongly suggested as valid candidates able to overcome Artificial Neural Networks (ANNs) in this specific contest. In this study, the proposal involves the ...
Added: December 12, 2024
Fadeeva T., Staruseva-Persheeva A., Pronina A., Артикульт 2024 № 1(53) С. 48–63
The rapid development of technoscience calls into question the usual ways of perception and traditional practices of information analysis, in particular, one of the challenges for the communication society has been the development of artificial intelligence capable of creating images that are almost indistinguishable from paintings and photographs, this is clearly visible in the discussions ...
Added: April 17, 2024