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News
August 25, 2026
Scientists Develop Algorithm for More Reliable Processors in Data Centres
Researchers from HSE MIEM and Samara University have developed the LRF-3D algorithm to automatically bypass idle nodes in three-dimensional networks-on-chip. Thanks to its hierarchical architecture, the algorithm outperforms existing solutions in both speed and path accuracy, improving processor reliability for use in data centres, supercomputers, and AI computing. The source code and test results are publicly available.
August 24, 2026
Researchers Develop Method for Direct Generation of Regulatory DNA
Researchers at HSE University have developed a model for generating promoters and enhancers—DNA sequences that regulate gene activity. The model works directly with DNA nucleotides, without first transforming them into a continuous numerical representation. This solution could be useful for applications in synthetic biology and gene therapy. The study results were presented at the ICLR 2026 Workshop ‘Generative AI in Genomics (Gen^2): Barriers and Frontiers.’
August 21, 2026
Social Integration: At the Crossroads of Knowledge and Values
The International Laboratory for Social Integration Research (ILSIR) at HSE University studies the challenges faced by vulnerable groups and explores ways to help them participate fully in everyday life. To develop effective solutions, the laboratory’s researchers combine cutting-edge methods with practical fieldwork. In this interview with the HSE News Service, Laboratory Head Elena Iarskaia-Smirnova discusses the laboratory’s work.

 

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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
Sample Chapter
Text on another site
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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