4 citations · 14 across the 9 of their papers we have counts for
9 papers
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…
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…
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…
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…
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…
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…
A Turning Band Approach to Kernel Convolution for Arbitrary Surfaces
Alexander Gribov
One of the most efficient ways to produce unconditional simulations is with the spectral method using fast Fourier transform (FFT) [1]. But this approach is not applicable to arbit…
Searching for a Compressed Polyline with a Minimum Number of Vertices
Alexander Gribov
There are many practical applications that require simplification of polylines. Some of the goals are to reduce the amount of information necessary to store, improve processing tim…
Approximate Fitting of a Circular Arc When Two Points Are Known
Alexander Gribov
The task of approximating points with circular arcs is performed in many applications, such as polyline compression, noise filtering, and feature recognition. However, the developm…