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Railway Traffic Lights Recognition System
Ch. 32. P. 199–203.
The article deals with the problem of collecting information about railway traffic lights located on the territory of the Russian Federation. To solve this problem, a trained neural network is used that detects railway traffic lights in high-definition images. These images were taken by a camera installed on a train carriage, continuously photographing the area around the track on the right side towards the train. As a result, a detector model of the specified objects was obtained on high-precision images. The paper proposes algorithms for determining the marking and GPS coordinates at a previously detected railway traffic light. The architecture of the information system has been developed, which will have to store complete information about railway traffic lights. The system should be able to quickly search for information and use this data to plan the maintenance of railway traffic lights.
Lebedev O. B., Черкасов Р. И., Известия ЮФУ. Технические науки 2025 № 5(247) С. 254–276
This paper considers the application of artificial intelligence technologies, in particular computer vision, in visual information processing systems. A comprehensive analysis of neural network approaches to solving computer vision problems is carried out, including systematization of key types of problems: image classification, object detection and semantic segmentation. The architectural principles of convolutional neural networks are ...
Added: September 10, 2026
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
Зуенко Д. О., Trofimova E., Хайдарова И., IEEE Access 2026 Vol. 14 P. 121339–121357
Oil spill segmentation in Synthetic Aperture Radar (SAR) images is limited by noisy annotations in publicly available datasets and by architectural choices that interact with label quality in opposing directions. First, we introduce a manually refined version of the Deep-SAR Oil Spill (SOS) dataset, in which 36.25% of masks are corrected for false positives, missed ...
Added: September 7, 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
Kaznacheev P. A., Indakov G. S., Podymova N. B. et al., Izvestiya - Physics of the Solid Earth 2026 Vol. 61 P. 68–80
The paper discusses methods for estimating the grain size of polycrystalline materials based on the analysis of optical microscopic images, as well as the possibility of applying these methods to the analysis of rock textures. A comparison of the results obtained using several methods on a single sample of metamorphosed sandstone from the Northern Ladoga ...
Added: August 31, 2026
Gamberov T., Safin R., Chebotareva E. et al., , in: 2025 9th International Conference on Information, Control, and Communication Technologies (ICCT-2025).: IEEE, 2025. P. 1–5.
Digital human models (DHM) for virtual environments allow a cost-effective and reproducible evaluation of computer vision algorithms that are employed in robotics, e.g., human detection, tracking and following. Yet, many popular robotics simulators do not achieve a reasonable level of realism and diversity required to rigorously test such algorithms under varying conditions. This paper introduces ...
Added: June 23, 2026
Seul: PMLR, 2026.
Added: June 4, 2026
Slivnitsin P., Mylnikov L., Engineering Applications of Artificial Intelligence 2026 Vol. 179 Article 115185
The paper describes a applied artificial intelligence task of recognition-by-components method of real objects based on the recognition of a limited set of primitives or components. The recognition-by-components makes it possible to determine the components, that compose an object, and increase the number of recognizable objects without degrading the recognition quality. Training is performed on ...
Added: May 29, 2026
Davydov S. G., Федоров В. В., Социологические исследования 2026 № 5 С. 141–147
Представлены результаты измерения ИИ-грамотности взрослого населения России. Исследование решает проблему отсутствия эмпирических данных о фактическом уровне владения компетенциями в сфере искусственного интеллекта среди граждан. Методика основана на самооценке владения пятью типами ИИ-инструментов по 5‑балльной шкале и последующем индексировании. Сбор информации осуществлен методом телефонного опроса (CATI) на общероссийской выборке проекта «ВЦИОМ–Спутник» (N = 1600). Выявлен уровень ...
Added: May 13, 2026
Vasilev A., Kapitanov A., Roman Solovyev et al., PeerJ Computer Science 2026 Vol. 12 Article 3724
This article introduces MinMAE, a novel activation calibration method for Post-Training Quantization (PTQ) that significantly reduces accuracy loss in Convolutional Neural Networks (CNN). Motivated by the need for high-fidelity quantization without costly retraining, MinMAE directly minimizes the Mean Absolute Error (MAE) between original and dequantized activations, making it robust to outliers that degrade standard methods. ...
Added: May 3, 2026
Karpukhin I., Shipilov F., Savchenko A., Neurocomputing 2026 Vol. 672 Article 132771
Forecasting multiple future events within a given time horizon is essential for applications in finance, retail,
social networks, and healthcare. This problem is typically addressed using Marked Temporal Point Processes
(MTPP), which provide a principled framework for modeling both event timing and event labels. While most
existing research focuses on predicting only the next event, forecasting distant future ...
Added: February 25, 2026
Moshkin A., Лапутин Ф. А., Сидоров И. В., DIGITAL DIAGNOSTICS 2024 Т. 5 № S1 С. 40–42
BACKGROUND: Ovarian reserve reflects a woman's ability to successfully realize reproductive function. The assessment of ovarian reserve is an urgent task for clinical practice [1] and is important in scientific research. The use of computerized diagnostic image processing methods can accelerate and facilitate the performance of routine tasks in clinical practice. Their use in retrospective ...
Added: February 21, 2026
Pikul A. S., Безопасность информационных технологий 2024 Т. 31 № 4 С. 116–127
This article explores the potential use of modern computer vision architectures for the task of deepfake detection. The following architectures are considered: EfficientNet, Vision Transformer (ViT), VisionLSTM (ViL), Vision KAN, and Mamba Vision. The novelty of the approach lies in the application and comparison of these architectures, as well as their combination into paired ensembles ...
Added: December 12, 2025
Dzhanashia K., Aleksandr Fedosov, Oleg Evsutin, Sensors 2025 Vol. 25 No. 23 Article 7726
Using an attack-simulation module is a well-recognized approach to improving the robustness of end-to-end neural-network-based data-hiding schemes. However, most proposed attack simulators are limited in the types of attacks they cover, usually handling only a basic set of digital transformations. Real, in-demand use cases for data-hiding methods may involve modifications that cannot be modeled by ...
Added: November 28, 2025
O.A. Goryunov, Maslennikov O. V., Kiselev M. V. et al., Chaos, Solitons and Fractals 2026 Vol. 203 Article 117663
Training complex, biologically plausible Spiking Neural Networks (SNNs) with local learning rules is a significant challenge for theoretical analysis. Here we address this problem by developing a comprehensive analytical theory for the learning dynamics of CoLaNET, a recently proposed columnar SNN. In particular, we consider a simplified model that captures the core algorithmic logic of ...
Added: November 28, 2025
Pakshin P., Актуальные проблемы российского права 2025 Т. 20 № 11 С. 11–18
The paper substantiates the necessity of providing legal protection for the results of intellectual works created by artificial intelligence through the mechanism of related rights. It examines ways to reduce legal risks associated with the creation of intellectual property using artificial intelligence technologies and offers a philosophical and legal analysis of the proposed hypothesis, namely, ...
Added: November 27, 2025
[б.и.], 2026.
The Winter Conference on Applications of Computer Vision is the premier international computer vision event comprising the main conference and several co-located workshops and tutorials. With its high quality and low cost, it provides an exceptional value for students, academics and industry researchers. ...
Added: November 24, 2025
Prikhodko R., Moshkin A., Romanov A., , in: 2025 International Russian Automation Conference (RusAutoCon).: IEEE, 2025. P. 273–278.
The vertebral arteries are one of the most important sources of blood supply to the brain, therefore any pathological changes in them can be the reason behind serious diseases. Magnetic Resonance Imaging (MRI) allows diagnosticians to examine main arteries, which is exceptionally important for effective diagnosis. However, because of the small size of arteries relative ...
Added: November 6, 2025
Dalian: IEEE, 2025.
The increasing complexity of modern software development necessitates intelligent, automated security analysis frameworks that can effectively pay attention of human on high-risk software releases. This paper introduces a Multi Agent System (MAS) framework designed to enhance the security assessment process by leveraging artificial intelligence (AI) and intelligent computing for real-time release analysis. The proposed system ...
Added: November 3, 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