Sentence examples for classification of points from inspiring English sources

Specifically, our workflow is implemented by five major steps, including preprocessing of the point cloud, division of building facades, classification of points, geometric modeling and refinement of results.

The other part relates to the point feature derivation using a novel 3D local feature descriptor LSSHOT, designed for extracting features in the classification of points.

For the classification of points using LSSHOT descriptor and a random forest classifier, the accuracy of results for the points of two major scaffolding elements reaches more than 70% in our test examples.

The jump operators and allow the classification of points in a time scale in the following way.

The following classification of points is used within the theory: a point (tinmathbb{T}) is called right-dense, right-scattered, left-dense and left-scattered if (sigma(t)=t), (sigma(t)>t), (rho(t)=t), and (rho(t)< t), respectively.

The jump operators σ and ρ allow the classification of points in (mathbb{T}) in this manner: if (sigma(t)>t), we say that t is right-scattered, while if (rho(t)< t) we say that t is left-scattered.

An important step in the automated Scan-to-BIM procedure is the interpretation and classification of point cloud data.

Automated classification of point clouds has received much attention with respect to LIDAR/laser scanning in complex natural settings44,45,46,47, but extension to very high-resolution photogrammetry-derived point clouds has also been successful48.

On the other side, the classification of point clouds by roughness index seems promising for recording the grading of the sediments.

Local models are a way to transform edge-prediction problems into well-known binary classification problems of points with labels.

Classification of data points for each time course was performed automatically by a corresponding algorithm (see Supplementary Materials & Methods).