An Integrated Framework for Road Detection in Dense Urban Area from High-Resolution Satellite Imagery and Lidar Data

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ISSN Print: 2151-1950
ISSN Online: 2151-1969
www.scirp.org/journal/jgis
E-mail: jgis@scirp.org

"An Integrated Framework for Road Detection in Dense Urban Area from High-Resolution Satellite Imagery and Lidar Data"
written by Asghar Milan,
published by Journal of Geographic Information System, Vol.10 No.2, 2018

has been cited by the following article(s):

[1]	Automatic building extraction on satellite images using unet and resnet50
	Computational Intelligence and Neuroscience, 2022

[2]	Extracting urban road footprints from airborne LiDAR point clouds with PointNet++ and two-step post-processing
	Remote Sensing, 2022

[3]	A Deep Learning-Based Classifier for Remote Sensing Images
	… Intelligence in Data Mining: Proceedings of ICCIDM …, 2022

[4]	Deep Learning-Based Classification Methods for Remote Sensing Images in Urban Built-Up Areas
	2019

[1]	Extracting Urban Road Footprints from Airborne LiDAR Point Clouds with PointNet++ and Two-Step Post-Processing Remote Sensing, 2022 DOI:10.3390/rs14030789

[2]	Automatic Building Extraction on Satellite Images Using Unet and ResNet50 Computational Intelligence and Neuroscience, 2022 DOI:10.1155/2022/5008854

[3]	Deep Learning-Based Classification Methods for Remote Sensing Images in Urban Built-Up Areas IEEE Access, 2019 DOI:10.1109/ACCESS.2019.2903127

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