Detecting road network errors from trajectory data with partial map matching and bidirectional recurrent neural network model-Reference-Cited by-同舟云学术

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Detecting road network errors from trajectory data with partial map matching and bidirectional recurrent neural network model

Published:2024-01-24 Issue:3 Volume:38 Page:478-502
ISSN:1365-8816
Container-title:International Journal of Geographical Information Science
language:en
Short-container-title:International Journal of Geographical Information Science

Author:

Yang Can¹^ORCID,Yue Peng¹²³,Gong Jianya¹,Li Jian⁴⁵,Yan Kai⁴⁵

Affiliation:

1. School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, PR China

2. Hubei LuoJia Laboratory, Wuhan, PR China

3. Hubei Province Engineering Center for Intelligent Geoprocessing (HPECIG), Wuhan University, Wuhan, PR China

4. State Key Laboratory of Intelligent Vehicle Safty Technology, Chongqing, PR China

5. Chongqing Changan Automobile Co. Ltd, Chongqing, PR China

Funder

National Natural Science Foundation of China

Chongqing Technology Innovation and Application Development Project

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/13658816.2024.2306158

Reference39 articles.

1. OSMnx: New methods for acquiring, constructing, analyzing, and visualizing complex street networks

2. Road Closure Detection based upon Multi-feature Fusion

3. Fast LIDAR-based road detection using fully convolutional neural networks

4. From GPS traces to a routable road map

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Urban Road Surface Condition Sensing from Crowd-Sourced Trajectories Based on the Detecting and Clustering Framework;Sensors;2024-06-24

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