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September 22, 2026
Personal Interest in Doctoral Thesis Topic Most Important for Confidence in Successful Defence
A researcher at HSE University analysed data on 1,539 doctoral students from 161 Russian universities to identify which features of a thesis topic are associated with academic success and engagement. The most important factor was found to be personal interest in the research topic, which was associated with almost all key aspects of doctoral programme experience—from engaging with the academic supervisor to research activity and confidence about successfully defending the thesis. The findings have been published in Higher Education.
September 21, 2026
Researchers Develop Methodology to Assess the Quality of Legal Representation in Criminal Proceedings
Having a good defence attorney in criminal proceedings can largely determine whether a defendant retains their freedom, health and good name. Researchers at HSE University propose a method for predicting an attorney’s performance based on the outcomes of their previous cases. The methodology takes into account the severity of the charges, the complexity of the cases, and the most likely outcome, drawing on judicial statistics.
September 21, 2026
Algebra, Geometry, and AI: Russian and Vietnamese Mathematicians Discuss Current Research
A delegation of scientists from Hanoi visited the HSE Faculty of Computer Science and then took part in a Russian-Vietnamese conference in St Petersburg. The events were part of the three-year project ‘Flexibility and Computational Methods.’ Over the course of the project, the researchers have prepared joint publications and obtained new mathematical results.

 

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2018 proceedings of European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2018),Bruges (Belgium), 25-27 April 2018

ESANN, 2018.

2018 proceedings of European Symposium on Artificial Neural Networks, Computational  Intelligence and Machine Learning (ESANN 2018),Bruges (Belgium), 25-27 April 2018 discusses the problems of  deep learning and image processing, regression and recommendation systems, Extreme Minimal Learning Machine, Neural networks, Facial emotion recognition.   

Chapters
Pollen Grain Recognition Using Convolutional Neural Network
Khanzhina N., Putin E., Filchenkov A. et al., , in: 2018 proceedings of European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2018),Bruges (Belgium), 25-27 April 2018.: ESANN, 2018. P. 409–414.
This paper addresses two problems: the automated pollen species recognition and counting them on an image obtained with a lighting microscope. Automation of pollen recognition is required in several domains, including allergy and asthma prevention in medicine and honey quality control in the nutrition industry. We propose a deep learning solution based on a convolutional neural network for classification, feature extraction ...
Added: January 21, 2019
Research target: Engineering and Technology
Language: English
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Keywords: automatic image recognitionartificial neural networksBernoulli convolutiondeep machine learning
2018 proceedings of European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2018),Bruges (Belgium), 25-27 April 2018
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Currently, artificial intelligence methods are widely used in the practice of serial production enterprises. They are used to detect defects, classify and eliminate them, identify the causes of defects, predict the quality and properties of the resulting product, select optimal parameters of the production process, and identify and study its patterns. However, outside the field ...
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