V. Berikov

V. Berikov, A. Tulupov, S. Alyamkin, 2022, 2022 Ural-Siberian Conference on Computational Technologies in Cognitive Science, Genomics and Biomedicine (CSGB).

Some properties of the classification algorithms using ensemble kernels

N Odinokikh, V Berikov, V. Berikov, 2021 .

Identification of unknown parameters and prediction with hierarchical matrices pdf

Alexander Litvinenko, Ronald Kriemann, Vladimir Berikov, 2021, 4th International Conference on Uncertainty Quantification in Computational Sciences and Engineering.

Cluster Ensemble Kernel for Kernel-based Classification

Vladimir Berikov, Nikita Odinokikh, V. Berikov, 2019, 2019 International Multi-Conference on Engineering, Computer and Information Sciences (SIBIRCON).

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

Vladimir B. Berikov, V. Berikov, 2019, MOTOR.

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

Alexander Litvinenko, Vladimir B. Berikov, V. Berikov, 2019, Proceedings of the 3rd International Conference on Uncertainty Quantification in Computational Sciences and Engineering (UNCECOMP 2019).

Group approach to solving the tasks of recognition

V. B. Berikov, Yedilkhan Amirgaliyev, Lyailya S. Cherikbayeva, 2019, Yugoslav Journal of Operations Research.

Regression Analysis with Cluster Ensemble and Kernel Function

Vladimir B. Berikov, Taisiya Vinogradova, V. Berikov, 2018, AIST.

Semi-supervised classification with cluster ensemble

Vladimir Berikov, Nikita Karaev, Ankit Tewari, 2017, 2017 International Multi-Conference on Engineering, Computer and Information Sciences (SIBIRCON).

Regression trees for analysis of mutational spectra in nucleotide sequences

Igor B. Rogozin, V. B. Berikov, I. Rogozin, 1999, Bioinform..

A Probabilistic Model of Fuzzy Clustering Ensemble

V. B. Berikov, V. Berikov, 2018, Pattern Recognition and Image Analysis.

V. B. Berikov, I A Pestunov, R M Kozinets, 2019, Journal of Physics: Conference Series.

Artificial intelligence in diabetology

V. B. Berikov, O. V. Saik, V. V. Klimontov, 2021, Diabetes mellitus.

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

Alexander Litvinenko, Vladimir Berikov, V. Berikov, 2021, ArXiv.

Hierarchical clustering algorithms for segmentation of multispectral images

I. A. Pestunov, V. B. Berikov, Sergey A. Rylov, 2015 .

Hierarchical clustering algorithms for segmentation of multispectral images

V. Berikov, I. Pestunov, S. Rylov, 2015, Optoelectronics, Instrumentation and Data Processing.

Computationally efficient methods of clustering ensemble construction for satellite image segmentation

V. B. Berikov, Sergey A. Rylov, Yuriy N. Sinyavskiy, 2017 .

Comparative Analysis of Deep Neural Network and Texture-Based Classifiers for Recognition of Acute Stroke using Non-Contrast CT Images

Vladimir Berikov, Victor Nedel’ko, Roman Kozinets, 2020, 2020 Ural Symposium on Biomedical Engineering, Radioelectronics and Information Technology (USBEREIT).

Model and Method for Constructing a Heterogeneous Cluster Ensemble

V. Berikov, 2022, Automation and remote control.

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

Vladimir B. Berikov, Igor Pestunov, V. Berikov, 2017, Pattern Recognit..

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

V. Berikov, I. Pestunov, A. Tulupov, 2023, Computer Optics.

Collective Distances for Clustering N-Valued Logic Formulas Representing Knowledge Base of Intellectual System

Vladimir Berikov, Alexander Vikent'ev, Michail Serov, 2019, 2019 International Multi-Conference on Engineering, Computer and Information Sciences (SIBIRCON).