activity
20152026
most citedReconstruction of Power Lines from Point Clouds

4 citations · 5 across the 4 of their papers we have counts for

collaborators

7 papers

cs.CV2026

Rail Track Extraction from Rasterized Classified Point Clouds Using a Full-Resolution, Fully Convolutional Recurrent Neural Network

Alexander Gribov, Jie Chang

Rail track extraction is essential for effective railway asset management and maintenance, especially in automated inspection and mapping workflows. This paper introduces a novel m…

cs.CG2025

Efficient Computation of the Directional Extremal Boundary of a Union of Equal-Radius Circles

Alexander Gribov

This paper focuses on computing the directional extremal boundary of a union of equal-radius circles. We introduce an efficient algorithm that accurately determines this boundary b…

cs.CV2022★ 4 cited

Reconstruction of Power Lines from Point Clouds

Alexander Gribov, Khalid Duri

This paper proposes a novel solution for constructing line features modeling each catenary curve present within a series of points representing multiple catenary curves. The soluti…

stat.CO2017★ 1 cited

New Flexible Compact Covariance Model on a Sphere

Alexander Gribov, Konstantin Krivoruchko

We discuss how the kernel convolution approach can be used to accurately approximate the spatial covariance model on a sphere using spherical distances between points. A detailed d…

cs.CG2016

Optimal Compression of a Polyline with Segments and Arcs

Alexander Gribov

This paper describes an efficient approach to constructing a resultant polyline with a minimum number of segments and arcs. While fitting an arc can be done with complexity O(1) (s…

stat.CO2016

Efficient Kernel Convolution for Smooth Surfaces without Edge Effects

Alexander Gribov

One of the most efficient ways to produce unconditional simulations is with the kernel convolution using fast Fourier transform (FFT) [1]. However, when data is located on a surfac…