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Segmenting Prostate Cancer on TRUS Images with a Small Dataset: A Comprehensive Methodology
P. 454–459.
The use of mathematical algorithms for disease identification has gained traction in recent years and has paved the way for the creation of novel tools that can swiftly and accurately detect pathologies. In particular, modern machine learning techniques have garnered significant attention in this domain and are currently among the most widely used algorithms. Despite their popularity, the implementation and training of these neural networks can be daunting, owing to the intricate nature of the data and the complexity of the training process. To address these challenges, this paper suggests an efficient neural network training algorithm that employs iterative analysis and gradient computation for each data packet, thus ensuring the attainment of optimal quality metrics.
In book
Sochi: IEEE, 2023.
Новиков Р. С., Novopashin M., Pozin B., Programming and Computer Software 2026 Vol. 52 No. 1 P. 28 – 38
Added: June 26, 2026
Seul: PMLR, 2026.
Added: June 4, 2026
Krasnov L., Malikov D., Kiseleva M. et al., Journal of Medicinal Chemistry 2026 Vol. 69 No. 8 P. 8838–8851
In this work, we developed a straightforward data-driven approach to predict the cytotoxicity of metal complexes based entirely on their (metal + ligands) composition. To this end, we have manually curated MetalCytoToxDB─a comprehensive experimental database comprising 26,500 IC50 values for 7050 metal complexes against 754 cell lines from 1921 articles. Based on these, machine learning ...
Added: April 23, 2026
Plesovskikh A., Journal of Applied Economic Research 2023 Т. 22 № 2 С. 323–354
Modern studies widely discuss the role of special economic zones in stimulating the economic growth and development of Russia, generating the necessary investment flows and increasing the country's innovative potential by expanding production in high-tech sectors of the economy with high added value. The purpose of the study is to model the process of generating ...
Added: April 13, 2026
Pakshin P., Legal Issues in the Digital Age 2026 Vol. 7 No. 1 P. 32–48
Artificial intelligence plays a significant role in automation, minimizing human intervention in fields such as medicine, art, and law. Despite the historically close relationship between art and technology, generative AI has expanded the potential for creative activity. A significant catalyst for this process has been the proliferation of pre-trained AI systems, which have accelerated the ...
Added: March 31, 2026
Gabdrahmanov R., Tsoy T., Martinez-Garcia E. et al., , in: Proceedings of the 21st International Conference on Informatics in Control, Automation and Robotics - (Volume 1) ICINCO 2024.: SciTePress, 2024. P. 511–518.
Computer simulations are growing in popularity in robotics research due to their near-zero cost of error and lower labor intensity. One of necessary components of a simulation, in addition to a robot model, is a model of a world in which the robot operates. While it is always possible to construct a world model manually, ...
Added: March 17, 2026
Semenikhin T., Kornilov M., Pruzhinskaya M. et al., , in: 26th International Conference, DAMDID/RCDL 2024, Nizhny Novgorod, Russia, October 23–25, 2024, Revised Selected Papers. Data Analytics and Management in Data Intensive Domains. (CCIS, volume 2641).: Springer, 2026. P. 211–219.
We considered two fundamentally different approaches to real-bogus classification within the Zwicky Transient Facility survey data. The first approach is based on neural networks that take sequences of object images as input. The second approach uses features extracted from light curves and classical machine learning methods. Several models for both approaches were tested. Quality metrics ...
Added: March 11, 2026
Maltseva S. V., Бериков В. Б., Кладов Д. Е. et al., В кн.: Информатика и прикладная математика: Материалы X Международной научно-практической конференции (08.10 - 11.10.2025 г.)Т. 1: Сборник материалов часть 1.: Алматы: Институт информационных и вычислительных технологий КН МНВО РК, 2025. С. 227–232.
This paper examines the problem of clustering consumption patterns for a private household. An ensemble algorithm based on the Wasserstein metric was developed and applied to cluster daily load profiles. The proposed approach allows for identifying typical energy consumption scenarios and interpreting consumer behavior. Results from computational experiments using real data are presented. ...
Added: March 3, 2026
Arinin O. V., Bakhmach D. M., Katsnelson A. et al., , in: 2025 Systems of Signals Generating and Processing in the Field of on Board Communications.: IEEE, 2025. P. 1–5.
This research discusses the method of dataset collection automatization for microwave filter synthesis by integrating machine learning techniques, thus reducing development time. Utilizing the 3D electromagnetic analysis software package, the study involves simulation and collecting geometric parameters and amplitude-frequency characteristics from three variants of passband highly selective microstrip tworesonator combined filters with stepped impedance resonators. ...
Added: December 6, 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
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
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
Cham: Springer, 2025.
This book constitutes the refereed proceedings of 34th International Workshops which were held in conjunction with the 34th International Conference on Artificial Neural Networks and Machine Learning, ICANN 2025, held in Kaunas, Lithuania, September 9–12, 2025.
The 20 full papers and 8 abstracts included in this workshop volume were carefully reviewed and selected from 42 submissions. ...
Added: September 29, 2025
Индаков Г. С., Казначеев П. А., Майбук З. Я. et al., Геофизические исследования 2025 Т. 26 № 2 С. 99–124
The paper studies the clusterability of acoustic emission pulses during high-temperature heating of sandstone sample preliminarily subjected to mechanical loading. Mechanical loading was applied in uniaxial mode up to load close to destructive with appearance of signs of large cracks on the surface. After that, samples were subjected to thermal treatment up to 650 °C ...
Added: September 19, 2025
Chepikov I., Karpov I., , in: 26th International Conference, AIED 2025, Palermo, Italy, July 22–26, 2025, Proceedings, Part I. Artificial Intelligence in Education. Posters and Late Breaking Results, Workshops and Tutorials, Industry and Innovation Tracks, Practitioners, Doctoral Consortium, Blue Sky, and WideAIED.: Springer, 2025. P. 352 – 358.
Modern LLM models such as BERT, ChatGPT, DeepSeek have shown great potential in solving various tasks, including text classification, text generation, analysis and summary of documents. In this paper, we show that these models close to classical ML approaches based on decision trees not only in text processing, but also in processing classical tabular data ...
Added: September 4, 2025