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News
May 25, 2026
HSE Scientists Train Neural Network to 'Hear' Faults in Electric Motors
Researchers at the AI and Digital Science Institute of the HSE Faculty of Computer Science have developed a new method—the Signature-Guided Data Augmentation (SGDA) framework—that achieves 99% accuracy in motor fault detection and 86% accuracy in fault classification. The application of this approach can reduce industrial equipment repair costs, minimise downtime, and improve production safety. The study results have been published in Engineering Applications of Artificial Intelligence.
May 25, 2026
'The Humanities Serve as a Conscience'
Maria Mizernaia studies Soviet literature and the history of book publishing. In this interview for the HSE Young Scientists project, she discusses plans to publish a novel about besieged Leningrad, AI-provoked reflections on what it means to be human, and how novels can help satisfy our dopamine hunger.
May 25, 2026
Is It Possible to Predict a Citys Life Based on the Shape of Its Neighbourhoods?
Is it possible to predict, based on the configuration of streets and buildings, where a café will open or where traffic congestion will occur? Participants in the Spatial Analysis and Modelling of Urban Processes research and study group use open data and machine learning to identify universal patterns. Alexander Sheludkov and Eduard Somov discuss the purpose of comparing cities, the need for new forms of urban statistics, and how open data is transforming approaches to urban studies.

 

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Proceedings of the 2019 European Conference on Mobile Robotics (ECMR 2019)

Prague : IEEE, 2019.
Editor-in-chief: L. Přeučil, S. Behnke, M. Kulich
Chapters
Real-time Vision-based Depth Reconstruction with NVidia Jetson
Bokovoy A., Muravyev K., Yakovlev K., , in: Proceedings of the 2019 European Conference on Mobile Robotics (ECMR 2019).: Prague: IEEE, 2019. P. 1–6.
Vision-based depth reconstruction is a challenging problem extensively studied in computer vision but still lacking universal solution. Reconstructing depth from single image is particularly valuable to mobile robotics as it can be embedded to the modern vision-based simultaneous localization and mapping (vSLAM) methods providing them with the metric information needed to construct accurate maps in ...
Added: January 15, 2020
Prioritized Multi-Agent Path Finding for Differential Drive Robots
Yakovlev K., Andreychuk A., Vorobyev V., , in: Proceedings of the 2019 European Conference on Mobile Robotics (ECMR 2019).: Prague: IEEE, 2019. P. 1–6.
Methods for centralized planning of the collision-free trajectories for a fleet of mobile robots typically solve the discretized version of the problem and rely on numerous simplifying assumptions, e.g. moves of uniform duration, cardinal only translations, equal speed and size of the robots etc., thus the resultant plans can not always be directly executed by ...
Added: January 15, 2020
Priority areas: IT and mathematics
Language: English
Text on another site
Keywords: Artificial Intelligence (incl. Robotics)
Proceedings of the 2019 European Conference on Mobile Robotics (ECMR 2019)
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Natural hazard database from Internet publications: text mining with a large language model
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Comprehensive data on natural hazards and their consequences are crucial for effective for risk assessment, adaptation planning, and emergency response. However, many countries face challenges with fragmented, inconsistent, and inaccessible data, particularly regarding local-scale events. To address this data gap in Russia, we developed an end-to-end processing pipeline that scrapes news from various online sources, ...
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