• A
  • A
  • A
  • АБВ
  • АБВ
  • АБВ
  • A
  • A
  • A
  • A
  • A
Обычная версия сайта
  • RU
  • EN
  • HSE University
  • Publications
  • Book chapter
  • Сегментация изображений с использованием древовидной аппроксимации кластеров в многомерном признаковом пространстве
  • RU
  • EN
Расширенный поиск
Высшая школа экономики
Национальный исследовательский университет
Priority areas
  • business informatics
  • economics
  • engineering science
  • humanitarian
  • IT and mathematics
  • law
  • management
  • mathematics
  • sociology
  • state and public administration
by year
  • 2028
  • 2027
  • 2026
  • 2025
  • 2024
  • 2023
  • 2022
  • 2021
  • 2020
  • 2019
  • 2018
  • 2017
  • 2016
  • 2015
  • 2014
  • 2013
  • 2012
  • 2011
  • 2010
  • 2009
  • 2008
  • 2007
  • 2006
  • 2005
  • 2004
  • 2003
  • 2002
  • 2001
  • 2000
  • 1999
  • 1998
  • 1997
  • 1996
  • 1995
  • 1994
  • 1993
  • 1992
  • 1991
  • 1990
  • 1989
  • 1988
  • 1987
  • 1986
  • 1985
  • 1984
  • 1983
  • 1982
  • 1981
  • 1980
  • 1979
  • 1978
  • 1977
  • 1976
  • 1975
  • 1974
  • 1973
  • 1972
  • 1971
  • 1970
  • 1969
  • 1968
  • 1967
  • 1966
  • 1965
  • 1964
  • 1963
  • 1958
  • More
Subject
News
September 25, 2026
AI Users Earn Up to 41.8% More Than Non-Users
Research conducted by economists at HSE University has revealed a significant correlation between the regular use of GenAI in the workplace and higher pay among Russian employees. The study found that individuals who frequently use GenAI in their professional activities earn notably more than those who reject these new tools or resort to them occasionally. The salary premium for highly qualified specialists reaches 41.8%. The article was published in the Voprosy Ekonomiki journal.
September 24, 2026
‘Feedback and Constructive Criticism Are Essential in Our Profession
Vincent Fardeau, Associate Professor at HSE ICEF, has reached a major career milestone: he recently published his paper ‘Asymmetric Thin Markets’ in the Journal of Financial Economics, successfully passed his major academic review, and received tenure. In this interview, Vincent discusses the story behind the paper, explains the concept of asymmetric thin markets, and shares his advice for young scholars aiming to publish in top-tier journals.
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.

 

Have you spotted a typo?
Highlight it, click Ctrl+Enter and send us a message. Thank you for your help!

Publications
  • Books
  • Articles
  • Chapters of books
  • Working papers
  • Report a publication
  • Research at HSE

?

Сегментация изображений с использованием древовидной аппроксимации кластеров в многомерном признаковом пространстве

С. 41–43.
Novikov N.
Language: Russian
Keywords: сегментация изображенийдревовидная аппроксимация кластеровмногомерное признаковое пространство

In book

Сборник конкурсных работ смотра-конкурса научно-технического творчества студентов высших учебных заведений «Эврика-2009»
Лик, 2010.
Similar publications
Instance Segmentation of Characters Recognized in Palmyrene Aramaic Inscriptions
Hamplová A., Lyavdansky A., Novák T. et al., CMES - Computer Modeling in Engineering and Sciences 2024 Vol. 140 No. 3 P. 2869–2889
This study presents a single-class and multi-class instance segmentation approach applied to ancient Palmyrene inscriptions, employing two state-of-the-art deep learning algorithms, namely YOLOv8 and Roboflow 3.0. The goal is to contribute to the preservation and understanding of historical texts, showcasing the potential of modern deep learning methods in archaeological research. Our research culminates in several ...
Added: July 17, 2024
Multispectral Remote Information in Forest Research
Пузаченко Ю. Г., Sandlerskiy R., Krenke A. et al., Russian Journal of Forest Science 2014 Vol. 7 No. 7 P. 838–854
The article proposes approaches to the use of multispectral remote information in basic research on the spatiotemporal organization of biogeocenotic cover with and without the use of ground field measurements. It is postulated that remote measurements reflect the biophysical condition of biogeocenotic cover defined by the absorption and conversion of solar energy and can be ...
Added: September 3, 2023
Theoretical and Methodological Substantiation of Boundaries and Integrity in Landscape Cover and Its Components
A. N. Krenke, R. B. Sandlersky, A. S. Baybar et al., Известия РАН. Серия биологическая. 2023 Vol. 50 No. 1 P. S85–S99
Four main models of the appearance of boundaries (in a particular case, integrity), arising from the theory of nonlinear dynamic systems, are considered briefly. On the basis of Kotelnikov’s fundamental sampling theorem and, accordingly, general information theory, the character of a distinguished boundary as a function of the sampling frequency in a spatial series with a ...
Added: December 2, 2022
Модель Мамфорда-Шаха сегментации графических изображений
Bulgakov S. A., В кн.: Научно-техническая конференция студентов, аспирантов и молодых специалистов НИУ ВШЭ. Материалы конференции.: М.: МИЭМ НИУ ВШЭ, 2014.
Рассматриваются методы сегментации графических изображений на основе модели Мамфорда-Шаха ...
Added: September 15, 2017
Deep Part-Based Generative Shape Model with Latent Variables
Kirillov A., Gavrikov M., Lobacheva E. et al., , in: Proceedings of the 27th British Machine Vision Conference.: -, 2016. P. 1–12.
The Shape Boltzmann Machine (SBM) and its multilabel version MSBM have been recently introduced as deep generative models that capture the variations of an object shape. While being more flexible MSBM requires datasets with labeled parts of the objects for training. In the paper we present an algorithm for training MSBM using binary masks of ...
Added: February 24, 2017
Многоклассовая модель формы со скрытыми переменными
Кириллов А. Н., Гавриков М. И., Lobacheva E. et al., Интеллектуальные системы. Теория и приложения 2015 Т. 19 № 2 С. 75–95
In this paper we consider the Shape Boltzmann Machine(SBM) and its multi-label version MSBM. We present an algorithm for training MSBM using only binary masks of objects and the seeds which approximately correspond to the locations of objects parts. ...
Added: September 30, 2015
К вопросу о бинаризации графических изображений
Istratov A., Bulgakov S. A., В кн.: Фундаментальные и прикладные исследования, разработка и применение высоких технологий в промышленности и экономикеТ. 2: Высокие технологии, исследования, образование, экономика.: СПб.: Издательство Политехнического университета, 2012. Гл. 4 С. 18–22.
This paper represents results of research on image thresholding techniques. Key words: image segmentation, image thresholding, otsu method, huang method, niblack method, triangle method. ...
Added: April 10, 2013
  • About
  • About
  • Key Figures & Facts
  • Sustainability at HSE University
  • Faculties & Departments
  • International Partnerships
  • Faculty & Staff
  • HSE Buildings
  • HSE University for Persons with Disabilities
  • Public Enquiries
  • Studies
  • Admissions
  • Programme Catalogue
  • Undergraduate
  • Graduate
  • Exchange Programmes
  • Summer University
  • Summer Schools
  • Semester in Moscow
  • Business Internship
  • Research
  • International Laboratories
  • Research Centres
  • Research Projects
  • Monitoring Studies
  • Conferences & Seminars
  • Academic Jobs
  • Yasin (April) International Academic Conference on Economic and Social Development
  • Media & Resources
  • Publications by staff
  • HSE Journals
  • Publishing House
  • iq.hse.ru: commentary by HSE experts
  • Library
  • Economic & Social Data Archive
  • Video
  • HSE Repository of Socio-Economic Information
  • HSE1993–2026
  • Contacts
  • Copyright
  • Privacy Policy
  • Site Map
Edit