Vladimir B. Berikov

According to our database, Vladimir B. Berikov authored at least 24 papers between 1999 and 2023.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2023

Acute ischemic stroke lesion segmentation in non-contrast CT images using 3D convolutional neural networks.

A. V. Dobshik, S. K. Verbitskiy, I. A. Pestunov, K. M. Sherman, Yu. N. Sinyavskiy, A. A. Tulupov, Vladimir B. Berikov

CoRR, 2023

Ensemble Clustering with Heterogeneous Transfer Learning.

Vladimir B. Berikov

Proceedings of the Analysis of Images, Social Networks and Texts, 2023

2022

Model and Method for Constructing a Heterogeneous Cluster Ensemble.

Vladimir B. Berikov

Autom. Remote. Control., December, 2022

ERANNs: Efficient residual audio neural networks for audio pattern recognition.

Sergey Verbitskiy, Vladimir B. Berikov, Viacheslav Vyshegorodtsev

Pattern Recognit. Lett., 2022

2021

Weakly supervised semantic segmentation of tomographic images in the diagnosis of stroke.

Anna Dobshik, Andrey Tulupov, Vladimir B. Berikov

CoRR, 2021

Identification of unknown parameters and prediction with hierarchical matrices.

Alexander Litvinenko, Ronald Kriemann, Vladimir B. Berikov

CoRR, 2021

Solving weakly supervised regression problem using low-rank manifold regularization.

Vladimir B. Berikov, Alexander Litvinenko

CoRR, 2021

Weakly Supervised Regression Using Manifold Regularization and Low-Rank Matrix Representation.

Vladimir B. Berikov, Alexander Litvinenko

Proceedings of the Mathematical Optimization Theory and Operations Research, 2021

On a Weakly Supervised Classification Problem.

Vladimir B. Berikov, Alexander Litvinenko, Igor Pestunov, Yuriy Sinyavskiy

Proceedings of the Analysis of Images, Social Networks and Texts, 2021

2020

Heterogeneous Transfer Learning in Ensemble Clustering.

Vladimir B. Berikov

CoRR, 2020

Recognition of Tomographic Images in the Diagnosis of Stroke.

Kirill Kalmutskiy, Andrey Tulupov, Vladimir B. Berikov

Proceedings of the Pattern Recognition. ICPR International Workshops and Challenges, 2020

2019

Semi-Supervised Regression using Cluster Ensemble and Low-Rank Co-Association Matrix Decomposition under Uncertainties.

Vladimir B. Berikov, Alexander Litvinenko

CoRR, 2019

Semi-supervised Classification Using Multiple Clustering and Low-Rank Matrix Operations.

Vladimir B. Berikov

Proceedings of the Mathematical Optimization Theory and Operations Research, 2019

2018

Regression Analysis with Cluster Ensemble and Kernel Function.

Vladimir B. Berikov, Taisiya Vinogradova

Proceedings of the Analysis of Images, Social Networks and Texts, 2018

2017

Ensemble clustering based on weighted co-association matrices: Error bound and convergence properties.

Vladimir B. Berikov, Igor Pestunov

Pattern Recognit., 2017

2016

Cluster Ensemble with Averaged Co-Association Matrix Maximizing the Expected Margin.

Vladimir B. Berikov

Proceedings of the Supplementary Proceedings of the 9th International Conference on Discrete Optimization and Operations Research and Scientific School (DOOR 2016), Vladivostok, Russia, September 19, 2016

2014

Weighted ensemble of algorithms for complex data clustering.

Vladimir B. Berikov

Pattern Recognit. Lett., 2014

2011

A Latent Variable Pairwise Classification Model of a Clustering Ensemble.

Vladimir B. Berikov

Proceedings of the Multiple Classifier Systems - 10th International Workshop, 2011

2009

Construction of the Ensemble of Logical Models in Cluster Analysis.

Vladimir B. Berikov

Proceedings of the Emerging Intelligent Computing Technology and Applications. With Aspects of Artificial Intelligence, 2009

2008

Bayesian Model of Recognition on a Finite Set of Events.

Vladimir B. Berikov, Gennady Lbov

Proceedings of the Artificial Intelligence: Theories, 2008

2007

Construction of an Event Tree on the Basis of Expert Knowledge and Time Series.

Gennady Lbov, Vladimir B. Berikov

Proceedings of the Knowledge Processing and Data Analysis - First International Conference, 2007

2003

The influence of prior knowledge on the expected performance of a classifier.

Vladimir B. Berikov, Alexander Litvinenko

Pattern Recognit. Lett., 2003

2002

An approach to the evaluation of the performance of a discrete classifier.

Vladimir B. Berikov

Pattern Recognit. Lett., 2002

1999

Regression trees for analysis of mutational spectra in nucleotide sequences.

Vladimir B. Berikov, Igor B. Rogozin

Bioinform., 1999