Deep Learning-Based Road Extraction From Historical Maps
Author:
Affiliation:
1. History Department, Koç University, Istanbul, Turkey
2. Department of Geomatics Engineering, Istanbul Technical University, Maslak, Sariyer, Turkey
Funder
H2020 European Research Council
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Electrical and Electronic Engineering,Geotechnical Engineering and Engineering Geology
Link
http://xplorestaging.ieee.org/ielx7/8859/9651998/09882054.pdf?arnumber=9882054
Reference19 articles.
1. Learning to Detect Roads in High-Resolution Aerial Images
2. Historical Map Applications and Processing Technologies
3. Automated Extraction of Human Settlement Patterns From Historical Topographic Map Series Using Weakly Supervised Convolutional Neural Networks
4. Automatic extraction of road intersection points from USGS historical map series using deep convolutional neural networks
5. Feature pyramid networks for object detection;lin;Proc IEEE Conf Comput Vision Pattern Recognit (CVPR),2022
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3. A novel framework for road vectorization and classification from historical maps based on deep learning and symbol painting;Computers, Environment and Urban Systems;2024-03
4. A critical analysis of road network extraction using remote sensing images with deep learning;Spatial Information Research;2024-02-27
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