Road Topology Extraction From Satellite Imagery by Joint Learning of Nodes and Their Connectivity

Author:

Zhang Jinming1ORCID,Hu Xiangyun2ORCID,Wei Yujun3ORCID,Zhang Lili1

Affiliation:

1. Key Laboratory of Network Information System Technology, Institute of Electronic, Chinese Academy of Sciences, Beijing, China

2. Hubei Luojia Laboratory, School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, China

3. China Railway First Survey and Design Institute Group Ltd., Xi’an, China

Funder

Special Fund of the Hubei Luojia Laboratory

Youth Innovation Promotion Association

Special Funds for Creative Research

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Earth and Planetary Sciences,Electrical and Electronic Engineering

Cited by 3 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. RUW-Net: A Dual Codec Network for Road Extraction From Remote Sensing Images;IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing;2024

2. L2T-BEV: Local Lane Topology Prediction from Onboard Surround-View Cameras in Bird’s Eye View Perspective;Pattern Recognition and Computer Vision;2023-12-24

3. Automatic Extraction of Road Networks by Using Teacher–Student Adaptive Structural Deep Belief Network and Its Application to Landslide Disaster;IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing;2023

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