نتایج جستجو برای: road network
تعداد نتایج: 733205 فیلتر نتایج به سال:
Road extraction using remote sensing images has been one of the most interesting topics for researchers in recent years. Recently, the development of deep neural networks (DNNs) in the field of semantic segmentation has become one of the important methods of Road extraction. In the Meanwhile The majority of research in the field of road extraction using DNN in urban and non-urban areas has been...
We study an important practical aspect of the route planning problem in real-world road networks – maneuvers. Informally, maneuvers represent various irregularities of the road network graph such as turn-prohibitions, traffic light delays, round-abouts, forbidden passages and so on. We propose a generalized model which can handle arbitrarily complex (and even negative) maneuvers and extend trad...
We describe and experimentally evaluate a system, FeasPar, that learns parsing spontaneous speech. The FeasPar architecture consists of neural networks and a search. The neural networks learns the parsing task, and the search improves performance by nding the most probable and consistent feature structure. This paper focuses on the search component, and shows how the search improves overall per...
This paper presents an automatic method for road network extraction from low-resolution images using hierarchical grouping technique. The method consists of three major steps: firstly it extracts line features from original images and generates smooth lines in a split-and-merge operation; a hierarchy of line images is created using different thresholds for line length, based on the generated li...
The inefficiencies arising from increased freight road traffic in the late 1990s in Mexico have posed to planners engaged in the road provision the goal to find new control measures to reduce the adverse impacts, such as road damage and overloading. In the 1990s, road freight traffic in Mexico altered notably after the deregulation of the road freight industry in 1989; the North American Free T...
In this paper, a new approach to road network extraction from multi-spectral (MS) imagery is presented. The proposed approach begins with an image segmentation using a spectral clustering algorithm. This step focuses on the exploitation of the spectral information for feature extraction. The road cluster(s) is automatically identified using a fuzzy classifier based on a set of predefined member...
This paper introduces a simulation designed to test real-time path planning done by single and multiple agents. The components of the simulation include a road network, several Uninhabited Aerial Vehicles (UAVs) with electro-optic sensors, a target and an Uninhabited Ground Vehicle (UGV). The target and UGV are located on the road network. Random blockages are placed on the road network, possib...
Urban road network traffic has become one of the most studied research topics in the last decades. This is mainly due to the enlargement of the cities and the growing number of motor vehicles traveling in this road network. One of the most sensitive problems is to verify if the network is congestion-free. Another related problem is the automatic reconfiguration of the network without building n...
Road extraction from satellite images is challenging research area in information extraction from high-resolution remote sensing images such as IKONOS and QUICKBIRD. The road from satellite images can be identified based on its geometric, spectral, topological and contextual properties as well as on various illumination and geographical environment. The road network extraction results in map ge...
In this paper, a new access method is proposed for current positions of moving objects on road networks in order to efficiently update their positions. In the existing index structures, the connectivity ofedges is lost because the intersection points in which three or more edges are split. The proposed index structure preserves the network connectivity, which uses intersection oriented network ...
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