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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.
Groshev Maksim, Rybakov Petr, Teterin N. et al., Sensors 2026 Article 6171
Manual assessment of soybean yield components, such as pod number, is laborious, time-consuming, and subjective. Existing computer-vision approaches based on object detection or instance segmentation perform poorly on close-range RGB imagery of soybean canopies due to severe occlusions, ambiguous plant boundaries, and the high cost of bounding-box annotation. To address these challenges, we propose a ...
Added: October 7, 2026
Rozhdestvenskaya E., Abramov R., Журнал социологии и социальной антропологии 2026 Т. 29 № 3 С. 244–274
The article presents an experimental study at the intersection of social anthropology and qualitative sociology. The empirical basis is a corpus of 18 short biographical sketches of collective farm peasant women from the village of Vysheley, Penza Region, created at the end of the Soviet period by school local historians and discovered by one of the authors during a ...
Added: October 7, 2026
Portnoy S., Efremov A., Voloshin A., , in: 2026 Systems of Signal Synchronization, Generating and Processing in Telecommunications (SYNCHROINFO).: Petrozavodsk: IEEE, 2026. P. 1–4.
This paper presents a deep learning-based optimization of a list-decoding algorithm for a concatenated Hamming-Reed-Solomon code transmitted over an AWGN channel with BPSK modulation. The proposed method reformulates early termination of the erasure-pattern list as a weighted regression problem, addressing class imbalance through an asymmetric Weighted Mean Squared Error (WMSE) loss function that penalizes index ...
Added: October 1, 2026
Aleksei Samarin, Nazarenko A., Alexander Savelev et al., Pattern Recognition and Image Analysis 2024 Vol. 34 No. 3 P. 844–854
Improving image quality is becoming an increasingly popular task, especially when working with mobile devices. One common approach to image enhancement is the use of convolutional neural networks. However, to achieve good results, such networks must be large enough, otherwise there is a risk of unwanted artifacts. In addition, large convolutional neural networks require significant ...
Added: September 21, 2026
Самарин А. В., Торопов А. Г., Савельев А. Г. et al., Pattern Recognition and Image Analysis 2024 Vol. 34 No. 4 P. 1044–1052
This paper presents a study aimed at improving the detection quality of small-sized microorganisms under challenging microscopic conditions through the application of a lightweight combined image preprocessing model. We focused on the task of detecting diplococci in images obtained through dynamic sample microscopy. The proposed approach employs predefined filters for image preprocessing, combined with the ...
Added: September 21, 2026
Aleksei Samarin, Aleksei Toropov, Alexander Savelev et al., , in: Pattern Recognition. ICPR 2024 International Workshops and Challenges. Kolkata, India, December 1, 2024, Proceedings, Part III. LNCS, volume 15616.: Cham: Springer, 2025. P. 308–320.
This research explores an innovative approach to enhancing the accuracy of detecting small microorganisms in complex microscopic environments. Our study introduces a streamlined, hybrid image pre-processing model specifically designed to address the challenges of identifying diplococci in live microscopy of dynamic samples. By integrating pre-defined filtering techniques with predictive adjustments for optimal applicability, our method ...
Added: September 21, 2026
Cham: Springer, 2026.
computer vision ...
Added: September 19, 2026
Aleksei Samarin, Aleksei Toropov, Dzestelova A. et al., , in: Proceedings of the 36th Conference of Open Innovations Association FRUCT, Helsinki, Finland, 30 October - 1 November 2024Vol. 36.: FRUCT Oy, 2024. P. 903–911.
In this work, we describe our research aimed at developing classifiers for microbial images (bacilli images) obtained through microscopy of live (non-static) samples. We employed our proposed approach called AutoML, which is based on the automatic generation and analysis of the feature space to create the most optimal descriptors for microscopic images used in their ...
Added: September 19, 2026
FRUCT Oy, 2024.
Added: September 19, 2026
Aleksei Samarin, Aleksei Toropov, Kotenko E. et al., , in: Proceedings of the 37th Conference of Open Innovations Association FRUCT, Helsinki, Finland, 14-16 May 2025, Issue 1 (Full Papers)Vol. 37.: Helsinki: FRUCT Oy, 2025. P. 278–284.
This study introduces an innovative method for recognizing automatically generated images by utilizing adapted descriptors specifically designed to analyze unique structural and morphological features characteristic of artificially created content. The methodology focuses on analyzing features inherent to image generation processes, ensuring the optimization of descriptors for identifying complex and subtle patterns associated with generative algorithms. ...
Added: September 19, 2026
Helsinki: FRUCT Oy, 2025.
Added: September 19, 2026
Helsinki: FRUCT Oy, 2026.
Added: September 19, 2026
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
Denis Zuenko, Khaidarova I., Trofimova E., 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
Vyacheslav D. Neverov, Lukyanov A., Andrey V. Krasavin et al., Physical Review B: Condensed Matter and Materials Physics 2026 Vol. 113 No. 2 Article 024515
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