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DeepStreet: A deep learning powered urban street network generation module
[article]
2020
arXiv
pre-print
In countries experiencing unprecedented waves of urbanization, there is a need for rapid and high quality urban street design. Our study presents a novel deep learning powered approach, DeepStreet (DS), for automatic street network generation that can be applied to the urban street design with local characteristics. DS is driven by a Convolutional Neural Network (CNN) that enables the interpolation of streets based on the areas of immediate vicinity. Specifically, the CNN is firstly trained to
arXiv:2010.04365v1
fatcat:uspe5g2dtzbjnmmzf67gg7dvvy