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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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No Advantage for Separating Overt and Covert Attention in Visual Search

Vision. 2020. Vol. 4. No. 2. P. 28.
MacInnes W., Jóhannesson Ó., Chetverikov A., Kristjánsson Á.

We move our eyes roughly three times every second while searching complex scenes, but covert attention helps to guide where we allocate those overt fixations. Covert attention may be allocated reflexively or voluntarily, and speeds the rate of information processing at the attended location. Reducing access to covert attention hinders performance, but it is not known to what degree the locus of covert attention is tied to the current gaze position. We compared visual search performance in a traditional gaze-contingent display, with a second task where a similarly sized contingent window is controlled with a mouse, allowing a covert aperture to be controlled independently by overt gaze. Larger apertures improved performance for both the mouse- and gaze-contingent trials, suggesting that covert attention was beneficial regardless of control type. We also found evidence that participants used the mouse-controlled aperture somewhat independently of gaze position, suggesting that participants attempted to untether their covert and overt attention when possible. This untethering manipulation, however, resulted in an overall cost to search performance, a result at odds with previous results in a change blindness paradigm. Untethering covert and overt attention may therefore have costs or benefits depending on the task demands in each case.

Research target: Psychology
Language: English
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DOI
Text on another site
Keywords: attentionvisual searchSaccadic eye movements
Publication based on the results of:
A computational model to simulate visual stability from eye movements and spatial attention (2017)
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