16 citations · 19 across the 6 of their papers we have counts for
6 papers
Acute ischemic stroke lesion segmentation in non-contrast CT images using 3D convolutional neural networks
A. V. Dobshik, S. K. Verbitskiy, I. A. Pestunov +4
In this paper, an automatic algorithm aimed at volumetric segmentation of acute ischemic stroke lesion in non-contrast computed tomography brain 3D images is proposed. Our deep-lea…
Weakly supervised semantic segmentation of tomographic images in the diagnosis of stroke
Anna Dobshik, Andrey Tulupov, Vladimir Berikov
This paper presents an automatic algorithm for the segmentation of areas affected by an acute stroke on the non-contrast computed tomography brain images. The proposed algorithm is…
Identification of unknown parameters and prediction with hierarchical matrices
Alexander Litvinenko, Ronald Kriemann, Vladimir Berikov
Statistical analysis of massive datasets very often implies expensive linear algebra operations with large dense matrices. Typical tasks are an estimation of unknown parameters of…
Solving weakly supervised regression problem using low-rank manifold regularization
Vladimir Berikov, Alexander Litvinenko
We solve a weakly supervised regression problem. Under "weakly" we understand that for some training points the labels are known, for some unknown, and for others uncertain due to…
Heterogeneous Transfer Learning in Ensemble Clustering
Vladimir Berikov
This work proposes an ensemble clustering method using transfer learning approach. We consider a clustering problem, in which in addition to data under consideration, "similar" lab…
Semi-Supervised Regression using Cluster Ensemble and Low-Rank Co-Association Matrix Decomposition under Uncertainties
Vladimir Berikov, Alexander Litvinenko
In this paper, we solve a semi-supervised regression problem. Due to the lack of knowledge about the data structure and the presence of random noise, the considered data model is u…