Wei Tu
12 Papers
Wei Tu is an academic researcher. The author has contributed to research in topics: Computer science & Population. The author has an hindex of 3, co-authored 11 publications.
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Papers
A hierarchical approach for fine-grained urban villages recognition fusing remote and social sensing data
TL;DR: Wang et al. as mentioned in this paper proposed a hierarchical recognition framework which can integrate remote and social sensing data to recognize fine-grained urban villages (UVs) in large cities with high-density urban areas where UV maps cannot be updated frequently.
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Automatic Tunnel Crack Inspection Using an Efficient Mobile Imaging Module and a Lightweight CNN
Jianghai Liao,Yuanhao Yue,Dejin Zhang,Wei Tu,Rui Cao,Qin Zou,Qingquan Li +6 more
- 01 Sep 2022
TL;DR: This study presents a new MTIS for fast tunnel crack inspection that consists of a novel mobile imaging module and an automatic crack detection module designed for efficient tunnel crack detection, with an effective spatial constraint strategy to guarantee crack continuity.
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Revealing transport inequality from an activity space perspective: A study based on human mobility data
TL;DR: In this article , the authors introduced people-based activity space approaches to measure activity disparities between the two modal groups, and found that people who use cars on average accessed more activities within a larger activity space and enjoyed overall higher travel efficiency.
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Fine-grained crowd distribution forecasting with multi-order spatial interactions using mobile phone data
TL;DR: In this article , a weighted random walk algorithm was applied to generate simulated trajectories for improving the interaction characterizations derived from sparse mobile phone data, and the multi-order spatial interactions among contextual non-adjacent places were modelled with an embedding learning technique.
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Measuring spatial nonstationary effects of POI-based mixed use on urban vibrancy using Bayesian spatially varying coefficients model
TL;DR: In this paper , a Bayesian spatially varying coefficient (SVC) model was proposed to explore the spatially nonstationary relationship between mixed land use and urban vibrancy after controlling for other factors.
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