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News
July 24, 2026
'Physics Is What the World Is Literally Built On'
Physicist Nina Dzhanayeva, recipient of a Vladimir Potanin Foundation scholarship, focuses her research on nanophotonics. In this interview for the HSE Young Scientists project, she discusses nanowells, scientific intuition, and how physics can help in making frangipane cream puffs.
July 20, 2026
Scientists Create Open Dataset for Studying Concentration
A team of Russian researchers, including scientists from HSE University–St Petersburg, has developed the first open multimodal dataset containing recordings of brain activity, heart function, and video observations to help researchers understand what happens in the human brain during deep concentration. In the future, the dataset could accelerate the development of neural interfaces, rehabilitation technologies, and AI systems. The article has been published in Scientific Data.
July 20, 2026
‘Science Is Universal-It Knows No Borders
Fuad Aleskerov, Tenured Professor and Director of the International Centre of Decision Choice and Analysis at HSE University, together with his colleagues, has developed methods of network analysis in bibliometrics that have made it possible to identify patterns in the appearance and citation of publications in academic journals, as well as their influence on each other. When one or a number of studies are frequently cited by a wide range of journals, this is an indicator that the research is of high quality. By contrast, extensive cross-citation within a limited group of journals increases the likelihood of identifying a network of predatory publications.

 

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Method of Directed Enumeration of Alternatives in the Problem of Automatic Recognition of Half-Tone Images

Optoelectronics, Instrumentation and Data Processing. 2009. Vol. 45. No. 3. P. 255–261.
Savchenko A.

The article deals with a problem of halftone image signals recognition using the minimum of the informative divergent criterion. The new algorithm of direct search among set of alternatives using Kullback-Leibler information distance has been developed in opposition to exhaustive search between concurrent hypotheses. The experimental results have been produced. The proposed algorithm is characterized by increased accuracy and assurance factor in the problem of automatic image recognition.

Research target: Mathematics Computer Science
Priority areas: business informatics
Language: English
Full text
Keywords: распознавание образовкритерий минимума информационного рассогласованияавтоматическое распознавание изображенийautomatic image recognitionpattern recognitionrecognition with trainingcriterion of the minimum of information mismatchраспознавание с обучениемобработка изображенийматематические проблемы искусственного интеллекта
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