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ORCIDComputers, Environment and Urban Systems, Volume 111
Volume 111, 2024
- Maya Mueller, Simi Hoque, Hamil Pearsall:
Machine learning to model gentrification: A synthesis of emerging forms. 102119 - Binyu Lei, Pengyuan Liu, Nikola Milojevic-Dupont, Filip Biljecki:
Predicting building characteristics at urban scale using graph neural networks and street-level context. 102129 - Xiangkai Zhou, Linlin You, Shuqi Zhong, Ming Cai:
From cell tower location to user location: Understanding the spatial uncertainty of mobile phone network data in human mobility research. 102130 - Madison Lore, Julia Gabriele Harten, Geoff Boeing
:
A hybrid deep learning method for identifying topics in large-scale urban text data: Benefits and trade-offs. 102131 - Zhou Fang, Ying Jin, Shuwen Zheng, Liang Zhao, Tianren Yang:
UrbanClassifier: A deep learning-based model for automated typology and temporal analysis of urban fabric across multiple spatial scales and viewpoints. 102132 - Changlan Yang, Xuefeng Guan, Qingyang Xu, Weiran Xing, Xiaoyu Chen, Jinguo Chen, Peng Jia:
How can SHAP (SHapley Additive exPlanations) interpretations improve deep learning based urban cellular automata model? 102133
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