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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.
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Исследование методов сжатия 3D-данных, для систем лазерного сканирования

С. 79–80.
Поляков С. В., Polyakov E. V.

This paper investigates the problem in the field of large volumes of 3D data. Existing methods of solution, analysis of the current state and features of systems for obtaining, representing and compressing spatial data are investigated.

Language: Russian
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Keywords: 3D-объект3D

In book

Межвузовская научно-техническая конференция студентов, аспирантов и молодых специалистов им. Е.В. Арменского
МИЭМ НИУ ВШЭ, 2018.
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