From 3D pedestrian networks to wheelable networks

An automatic wheelability assessment method for high-density urban areas using contrastive deep learning of smartphone point clouds

Bibliographic Data

ID7150592
AuthorsSiyuan Meng (0000-0003-3704-5918, University of Hong Kong), Xian Su (0000-0002-8295-876X, Guangxi Science and Technology Department), Guibo Sun (0000-0002-9476-1243, Manchester School of Architecture), Maosu Li (0000-0002-9970-4053, University of Hong Kong), Fan Xue (0000-0003-2217-3693, University of Hong Kong, corresponding author)
Year2025
Volume117
Pages102255
Publication date2025-04-01
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueComputers Environment and Urban Systems (JOURNAL)
Journal identifiersISSN: 0198-9715 • E-ISSN: 1873-7587
PublisherElsevier BV (PUBLISHER)
DOI10.1016/j.compenvurbsys.2025.102255
OpenAlexW4407152351
LanguageEN
Citations received1
References cited40

Tools

Open DOIOpen Access