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ORCIDLi Wan 0006
Person information
- affiliation: University of Cambridge, Department of Land Economy, Department of Architecture, UK
Other persons with the same name
- Li Wan — disambiguation page
- Li Wan 0001 — University of Melbourne, Department of Electrical and Electronic Engineering, Parkville, VIC, Australia,
- Li Wan 0002 — New York University, Department of Computer Science, Courant Institute of Mathematical Science, USA
- Li Wan 0003
![[0000-0002-0146-5163]](https://dblp.uni-trier.de/img/orcid-mark.12x12.png "0000-0002-0146-5163")
— Wuhan Textile University, School of Mathematics and Computer Science, China (and 3 more) - Li Wan 0004 — Google Inc., Google LLC., USA
- Li Wan 0005 — Huazhong University of Science and Technology, HUST, School of Mechanical Science and Engineering, Wuhan, China (and 1 more)
- Li Wan 0007 — Guangzhou University, School of Mathematics and Information Science, Guangdong, China
- Li Wan 0008 — Fudan University, State Key Laboratory of Integrated Chips and Systems, State Key Laboratory of ASIC and System, Shanghai, China (and 1 more)
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Journal Articles
- 2024
[j3]Junqing Tang, Jing Wang, Jiaying Li, Pengjun Zhao, Wei Lyu, Wei Zhai, Li Yuan, Li Wan, Chenyu Yang:
Predicting human mobility flows in response to extreme urban floods: A hybrid deep learning model considering spatial heterogeneity. Comput. Environ. Urban Syst. 113: 102160 (2024)- 2020
- [j2]Junqing Tang, Li Wan, Timea Nochta, Jennifer Schooling, Tianren Yang:
Exploring Resilient Observability in Traffic-Monitoring Sensor Networks: A Study of Spatial-Temporal Vehicle Patterns. ISPRS Int. J. Geo Inf. 9(4): 247 (2020) - 2018
- [j1]Li Wan, Shuo Gao, Chen Wu, Ying Jin, Mingrui Mao, Lei Yang:
Big data and urban system model - Substitutes or complements? A case study of modelling commuting patterns in Beijing. Comput. Environ. Urban Syst. 68: 64-77 (2018)
Conference and Workshop Papers
- 2020
- [c1]Zhou Fang, Jiaxin Qi, Tianren Yang, Li Wan, Ying Jin:
"Reading" cities with computer vision: a new multi-spatial scale urban fabric dataset and a novel convolutional neural network solution for urban fabric classification tasks. SIGSPATIAL/GIS 2020: 507-517
Coauthor Index
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