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The objective of this research is to detect points that describe a road surface in an unclassified point cloud of the airborne laser scanning (ALS). For this purpose we use the Random Forest learning ...
Occurrence of non-recurrent traffic congestion hinders the economic activity of a city, as travellers could miss appointments or be late for work or important meetings. Similarly, for shippers, unexpe...
The common method of LiDAR classifications is Markov random fields (MRF). Based on construction of MRF energy function, spectral and directional features are extracted for on-board urban point clouds....
Using data fusion of multi-spectral and microwave radar images, a semiautomatic method is developed based on the level set method for application to urban road extraction. The fast marching method of ...
or quickly populating GIS database, it is important to derive accurate and truly road information from imagery. In this paper, we describe the problem of urban road extraction from digital imagery u...
This paper focuses on internal quality measures for automatic road extraction from aerial images taken over urban areas. The motivation of this work is twofold: Firstly, any automatic system should p...
this paper develops a real-time traffic signal timing model which is to be integrated into a single intersection for urban road, thereby solving the problem of traffic congestion. We analyze the curre...
Traditional transport policies of road expansion entail a relatively simple system of actors and processes around which expertise, knowledge, and skills which has built up over many decades. Some of t...
In view of the fact that road network detection effect in high-resolution image is not satisfying, an approach for road network detection based on Bayesian Network is put forward in this paper. First,...
We study the structure of road networks across 425 cities of different sizes in the USA. We show decentralization as an important difference between urban road networks and biological vascular network...

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