Sentence examples for surfaces classification from inspiring English sources

For practical applications, in agreement with the ISO road roughness surfaces classification, it is possible to generate an artificial road profile from a stochastic representation, in terms of the function of Power Spectral Density (PSD) of vertical displacements obtained through the Fourier Transform of the auto-correlation function of the stochastic process describing the road profile.

In a separate step, surface classification operators are applied to obtain a partial opacity for every voxel.

In this paper, we investigate further its use for surface classification.

Following our design approach, we provide a classification system with a runner-independent surface classification rate of more than 80%.

The cloud mask and snow/ice discriminator are used for cloud clearing as well as surface classification.

We used airborne hyperspectral data from the AisaFENIX sensor for surface classification and ASD spectral measurements of soil samples for subsurface analysis.

This work is focused on the soil surface classification by implementing a visual system capable to distinguish between five usual types of off-road terrains.

In this paper the authors revisit recent publications which have considered surface classification in the light of new and emerging manufacturing techniques and have developed their ideas to provide more meaningful and comprehensive classifications of these surfaces.

This paper has researched the accuracy and interpretability of using the dimension reduction and coefficient shrinkage methods in combination with the logistic model to deal with this dimensionality problem in engineering surface classification.

In addition to signal strength, other signal characteristics such as those related to the observed correlation waveform may be used to enhance surface change detection or surface classification.

This approach of generating landforms from DEM is on the basis of applying a moving neighborhood analysis window and a land surface classification method modified from Hammond (1964).