activity
20062020
most citedDeep Learning for ECG Segmentation

55 citations · 85 across the 5 of their papers we have counts for

collaborators

9 papers

math.OC2020

A polynomial algorithm for minimizing discrete convic functions in fixed dimension

S. I. Veselov, D. V. Gribanov, N. Yu. Zolotykh +1

Recently classes of conic and discrete conic functions were introduced. In this paper we use the term convic instead conic. The class of convic functions properly includes the clas…

math.CO2020

How to Find the Convex Hull of All Integer Points in a Polyhedron?

S. O. Semenov, N. Yu. Zolotykh

We propose a cut-based algorithm for finding all vertices and all facets of the convex hull of all integer points of a polyhedron defined by a system of linear inequalities. Our al…

cs.NE2020

Evolutionary algorithms for constructing an ensemble of decision trees

Evgeny Dolotov, Nikolai Zolotykh

Most decision tree induction algorithms are based on a greedy top-down recursive partitioning strategy for tree growth. In this paper, we propose several methods for induction of d…

math.PR2020

Linear and Fisher Separability of Random Points in the d-dimensional Spherical Layer

Sergey Sidorov, Nikolai Zolotykh

Stochastic separation theorems play important role in high-dimensional data analysis and machine learning. It turns out that in high dimension any point of a random set of points c…

eess.SP202020 cited

Electrocardiogram Generation and Feature Extraction Using a Variational Autoencoder

V. V. Kuznetsov, V. A. Moskalenko, N. Yu. Zolotykh

We propose a method for generating an electrocardiogram (ECG) signal for one cardiac cycle using a variational autoencoder. Using this method we extracted a vector of new 25 featur…

eess.SP202055 cited

Deep Learning for ECG Segmentation

Viktor Moskalenko, Nikolai Zolotykh, Grigory Osipov

We propose an algorithm for electrocardiogram (ECG) segmentation using a UNet-like full-convolutional neural network. The algorithm receives an arbitrary sampling rate ECG signal a…