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Matching Road Network Combining Hierarchical Strokes and Probabilistic Relaxation Method

Lin Yang, Zejun Zuo, Run Wang, Yaqin Ye, Maosheng Hu
2014 Open Automation and Control Systems Journal  
One layer of hierarchical strokes generating from road spatial structure are selected at a match and the matched parts are used as a stable reference for the next layer.  ...  Aiming at the complex multisource road network matching modes, this paper proposed a road network matching method based on hierarchical stable strokes.  ...  Use the road extraction method in literature [19] to extract the first stroke layer, and then generate the adjacent stroke as the next stroke layer. 3) According to the prior knowledge of the two maps  ... 
doi:10.2174/1874444301406010268 fatcat:uhlxcmaihnd2tcdyexpv73vtga

Fisheye Map Using Stroke-Based Generalization for Web Map Services

Daisuke YAMAMOTO, Masaki MURASE, Naohisa TAKAHASHI
2018 IEICE transactions on information and systems  
We store strokes in a weighted stroke table, as given in Table 1 . We generate strokes from the road network of OpenStreetMap. We describe the algorithm to generate strokes.  ...  Murase [14] proposed an online generalization method that uses a stroke database for Web searches.  ...  Prior to coming to NIT, he was engaged in research on parallel processing, software engineering, and network computing at NTT Laboratories for 25 years. He received B.E. and  ... 
doi:10.1587/transinf.2017edp7014 fatcat:axbwogcp7vexdfbqu2gfgcnqde

Deep Graph Convolutional Networks for Accurate Automatic Road Network Selection

Jing Zheng, Ziren Gao, Jingsong Ma, Jie Shen, Kang Zhang
2021 ISPRS International Journal of Geo-Information  
The selection of road networks is very important for cartographic generalization.  ...  However, current selection methods, which are based on the theory of graphs or strokes, have low automaticity and are highly subjective.  ...  If the graph-based methods take the spatial features of roads into full consideration, the selection method based on strokes can consider the connectivity of the road network. Thomson et al.  ... 
doi:10.3390/ijgi10110768 fatcat:qdol4wfgdfarvie4ertf4grbri

A Representation Method for Complex Road Networks in Virtual Geographic Environments

Peibei Zheng, Hong Tao, Songshan Yue, Mingguang Wu, Guonian Lv, Chuanlong Zhou
2017 ISPRS International Journal of Geo-Information  
Generally, roads in road networks are organized in different linear map layers that are drawn by using different linear symbols (with different colours, widths, textures and other symbol attributes) according  ...  For the single-line approach, road networks can be drawn by using the symbol with one Stroke, and for the double-line approach, the symbol can be constructed by using two different Strokes (one for the  ...  For the single-line approach, road networks can be drawn by using the symbol with one Stroke, and for the double-line approach, the symbol can be constructed by using two different Strokes (one for the  ... 
doi:10.3390/ijgi6110372 fatcat:llvhdwiobzg4nnf7apjmn7g3qm

Road network selection for medium scales using an extended stroke-mesh combination algorithm

Stefan A. Benz, Robert Weibel
2014 Cartography and Geographic Information Science  
The road network snippet on the left in Figure 11 shows the settlement area layer used for generating the result shown on the right. The settlement areas now remain clearly recognizable.  ...  Settlement areas layer (left) used to generate a proper balance of segment elimination in urban and rural areas (right). Data: TLM3D © swisstopo.  ... 
doi:10.1080/15230406.2014.928482 fatcat:ulpti7folneybf5dxwktg2b2ei

Application of AHP to Road Selection

Yuan Han, Zhonghui Wang, Xiaomin Lu, Bowei Hu
2020 ISPRS International Journal of Geo-Information  
The generalized result at a scale of 1:200,000 by AHP-based methods better preserved the structure of the original road network compared with other methods.  ...  Our method also gives preference to roads with relatively significant contextual characteristics without interfering with the structure of the road network.  ...  However, Weiss and Weibel [13] used a series of hierarchical angle thresholds according to road classes. This solution generated more reasonable stroke networks.  ... 
doi:10.3390/ijgi9020086 fatcat:pubvqlomengunptwiptzs7mohm

An Advanced Road Structure Image Segmentation Method using Swt in Cnn

2019 VOLUME-8 ISSUE-10, AUGUST 2019, REGULAR ISSUE  
In this paper, the design of advanced road structure image segmentation approach using stroke width transformation (SWT) in convolution neural network (CNN) is proposed.  ...  The SWT will capture the images of road areas in effective way. Hence the propose system has various features which will determine the color, width and many other.  ...  To detect the road authors introduced a texture based on convolution neural network. By using the photo mosaic generation the images are segmented.  ... 
doi:10.35940/ijitee.b1028.1292s319 fatcat:6q5ynbljhfafhlg242pubkzc6a

A Deep Learning Approach to Urban Street Functionality Prediction Based on Centrality Measures and Stacked Denoising Autoencoder

Fatemeh Noori, Hamid Kamangir, Scott A. King, Alaa Sheta, Mohammad Pashaei, Abbas SheikhMohammadZadeh
2020 ISPRS International Journal of Geo-Information  
In our work, a Stacked Denoising Autoencoder (SDAE) predicts a street's functionality, then logistic regression is used as a classifier.  ...  Transportation research always considers street networks as a connection between different urban areas.  ...  The first time a Self-Organizing Map (SOM) neural network was used in city network generalization was by Kohonen [32] .  ... 
doi:10.3390/ijgi9070456 fatcat:efdlovmhpvckxln5cfqveejk6i

Evaluating map specifications for automated generalization of settlements and road networks in small-scale maps

Karolina Maja Sielicka, Izabela Karsznia
2019 Miscellanea Geographica: Regional Studies on Development  
Thus this paper aims to fulfil this gap by evaluating map specifications concerning settlement and road network generalizations.  ...  The results of the settlement and road network generalization for both 1:500 000 and 1:1 000 000 detail levels were compared with the maps designed manually by experienced cartographers.  ...  Most road generalization methods involve making a decision about which road segments (strokes) to leave and which to omit.  ... 
doi:10.2478/mgrsd-2019-0025 fatcat:6g2uesxwezay3ehmznk6nyo6eq

Road network selection for small-scale maps using an improved centrality-based algorithm

Roy Weiss, Robert Weibel
2014 Journal of Spatial Information Science  
In the task of deriving road networks for products at smaller scales, road network selection forms a prerequisite for all other generalization operators, and is thus a fundamental operation in the overall  ...  The objective of this work was to develop an algorithm for automated road network selection from a large-scale (1:10,000) to a small-scale database (1:200,000).  ...  Thanks are also due to Stefan Benz for conceptual discussions regarding the programming part of the project. www.josis.org IMPROVED CENTRALITY-BASED ROAD SELECTION FOR SMALL SCALES  ... 
doi:10.5311/josis.2014.9.166 fatcat:tspzclm4yfgoho2jyra4wq2ciu

SideInfNet: A Deep Neural Network for Semi-Automatic Semantic Segmentation with Side Information [article]

Jing Yu Koh, Duc Thanh Nguyen, Quang-Trung Truong, Sai-Kit Yeung, Alexander Binder
2020 arXiv   pre-print
To evaluate our method, we applied the proposed network to three semantic segmentation tasks and conducted extensive experiments on benchmark datasets.  ...  Inspired by the practicality and applicability of the semi-automatic approach, this paper proposes a novel deep neural network architecture, namely SideInfNet that effectively integrates features learnt  ...  Therefore, our maxpool layer uses a kernel size of 6 and a stride of 4 to achieve the desired size.  ... 
arXiv:2002.02634v4 fatcat:eafyqwatyrdvllvvus56hj5umi

Automatic License Plate Recognition from Live streaming using Stroke width Transform and Artificial Neural Network

Heena Kher, Hetal Patel, Tejendra Panchal
2019 International Journal of Darshan Institute on Engineering Research & Emerging Technology  
A license plate detection method was produced to find number plates from a live snap shots of a video stream showing the movement of all the vehicles in various conditions such as, non-uniform illumination  ...  In this composition, the detection of a license plate from an image, stroke width transform was applied and been simulated on live snapshots.  ...  Authors also grateful to Principal and Head, Electronics and Engineering division of the A. D. Patel Institute of Technology for continuous motivation, assistance and encouragement.  ... 
doi:10.32692/ijdi-eret/7.2.2018.1802 fatcat:lkmbcrrd4bbvviqjwywpbfkimi

A study on a vehicle semi-active suspension control system based on road elevation identification

Zhengcai Yang, Chuan Shi, Yinglin Zheng, Shirui Gu, Feng Chen
2022 PLoS ONE  
The semi-active suspension controller is constructed using a diagonal recursive neural network algorithm, and the neural network weight is trained using a genetic algorithm.  ...  In addition, a preview diagonal recursive neural network control strategy for semi-active suspension, based on the combination of road elevation information, is proposed.  ...  The layers of the neural network used in this study were as follows: (1) The first layer was the input layer, which had n input nodes.  ... 
doi:10.1371/journal.pone.0269406 pmid:35749570 pmcid:PMC9232168 fatcat:kzmbo5myandkdcyhcuhaizv7yy

A Hierarchical Matching Method for Vectorial Road Networks Using Delaunay Triangulation

Zejun Zuo, Lin Yang, Xiaoya An, Wenjie Zhen, Haoyue Qian, Songling Dai
2020 ISPRS International Journal of Geo-Information  
First, the entire urban road network is divided into three levels (L1, L2, L3) by using the principle of stroke.  ...  To fill this gap, this study proposes a novel hierarchical road network matching method based on Delaunay triangulation (DTRM).  ...  Geo-Inf. 2020, 7, x FOR PEER REVIEW 6 An example of hierarchical generation of a road network. Figure 2 . 2 An example of hierarchical generation of a road network.  ... 
doi:10.3390/ijgi9090509 fatcat:wvgtwfgncbgtflffao4mbilt3e

DeepStreet: A deep learning powered urban street network generation module [article]

Zhou Fang, Tianren Yang, Ying Jin
2020 arXiv   pre-print
Furthermore, the generated networks can serve as a benchmark to guide the local plan-making especially in rapidly developing cities.  ...  street networks in the centre and irregular road alignments farther afield.  ...  The existing urban street network is stroked, pixelized, and stored in the Road network Channel.  ... 
arXiv:2010.04365v1 fatcat:uspe5g2dtzbjnmmzf67gg7dvvy
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