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News
May 15, 2026
Preserving Rationality in a Period of Turbulence
The HSE International Laboratory for Logic, Linguistics and Formal Philosophy studies logic and rationality in a transformed world characterised by a diversity of logical systems and rational agents. The laboratory supports and develops academic ties with Russian and international partners. The HSE News Service spoke with the head of the laboratory, Prof. Elena Dragalina-Chernaya, about its work.
May 15, 2026
‘All My Time Is Devoted to My Dissertation
Ilya Venediktov graduated from the Master’s programme at the HSE Tikhonov Moscow Institute of Electronics and Mathematics through the combined Master’s–PhD track and is currently studying at the HSE Doctoral School of Engineering Sciences. At present, he is undertaking a long-term research internship at the University of Science and Technology of China in Hefei, where he is preparing his dissertation. In this interview, he explains how an internship differs from an academic mobility programme, discusses his research topic, and describes the daily life of a Russian doctoral student in China.
May 15, 2026
‘What Matters Is Not What You Study, but Who You Study with
Katerina Koloskova began studying Arabic expecting to give it up after a year—now she cannot imagine her life without it. In an interview for the Young Scientists of HSE University project, she spoke about two translated books, an expedition to Socotra, and her love for Bethlehem.

 

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Analysis of Deep Feature Matching Algorithms in UAV Visual Localization

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Prutyanov V., Тернов М. А., Костров Д. С.

The work presents an analysis of the application of deep learning-based methods for the keypoint extraction and matching in the context of map-aided UAV visual localization. A method for visual localization in three degrees of freedom is proposed, which employs pretrained SuperPoint and LightGlue networks for both short-term optical flow and global frame-to-map matching components. The ability of SuperPoint and LightGlue to refine a prediction of a less accurate location estimator without fine-tuning was estimated. The accuracy of the proposed method was evaluated and a detailed analysis of keypoint-based image matching algorithms was conducted on the AdM_UAV dataset. The performance evaluation of the proposed method was carried out on NVIDIA Jetson Orin Nano and shows acceptable results for real-time visual localization on this hardware platform.

Language: English
DOI
Keywords: computer visionUAVsatellite imageryvisual localizationkeypoint matching

In book

2024 International Russian Automation Conference (RusAutoCon)
IEEE, 2024.
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