Sentence examples for segmentation of road from inspiring English sources

Therefore, cluster analysis can assist the segmentation of road accidents.

Segmentation of road images is an important method of determining the driving area.

To solve these problems, we design a supervised deep auto-encoder (AE) model to complete the semantic segmentation of road environment images.

The proposed work consists of three stages: segmentation of road region, connected component-based operations used to extract the connected road component from segmented road region, and removal of unwanted non-road pixels using morphological operation.

In this paper, we proposed a framework that used K-modes clustering technique as a preliminary task for segmentation of 11,574 road accidents on road network of Dehradun (India) between 2009 and 2014 (both included).

The results are demonstrated in Fig. 8. Open image in new window Fig. 8 Candidate of road boundaries segmentation results a vertical filter, b horizontal filter, c candidate of road boundaries.

Although, researchers used segmentation of the data to reduce this heterogeneity using some measures such as expert knowledge, but there is no guarantee that this will lead to an optimal segmentation which consists of homogeneous groups of road accidents [2].

The first step in the algorithm consists in segmentation of an image into the road region and the other region that includes the remaining part of image ("non-road").

This method consists of four stages: segmentation of remotely sensed image; then extraction of road region based on shape and spectral feature; after that, application of multivariate adaptive regression splines to extract road centerline; finally, the use of connection algorithm to get complete road network.

The method includes segmentation of 1 m slices from the road, extraction of profiles, evaluation of roughness parameters, and K-means clustering.

First, the dark channel based image segmentation is proposed to distinguish a rough road region from complex background noise, which is envisioned to reduce the workload of road detection.