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1,122 results on '"Ye, Xinyue"'

202. Supplemental Material - Exploring Flood Mitigation Governance by Estimating First-Floor Elevation via Deep Learning and Google Street View in Coastal Texas

Author

Gao, Ge, Ye, Xinyue, Li, Shoujia, Huang, Xiao, Ning, Huan, Retchless, David, and Li, Zhenlong

Subjects
FOS: Social and economic geography, Geography, 120599 Urban and Regional Planning not elsewhere classified
Abstract

Supplemental Material for Exploring Flood Mitigation Governance by Estimating First-Floor Elevation via Deep Learning and Google Street View in Coastal Texas by Ge Gao, Xinyue Ye, Shoujia Li, Xiao Huang, Huan Ning, David Retchless and Zhenlong Li in Environment and Planning B: Urban Analytics and City Science

Published
2023
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215. Corrigendum to “Challenges, tasks, and opportunities in modeling agent-based complex systems”, Ecological Modeling, 2021, 457: 109,685, page 1–15

Author

An, Li, primary, Grimm, Volker, additional, Sullivan, Abigail, additional, Turner, B.L., additional, Malleson, Nicolas, additional, Heppenstall, Alison, additional, Vincenot, Christian, additional, Robinson, Derek, additional, Ye, Xinyue, additional, Liu, Jianguo, additional, Lindkvist, Emilie, additional, and Tang, Wenwu, additional

Published
2022
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218. Spatiotemporal Prediction of Theft Risk with Deep Inception-Residual Networks

Author

Ye, Xinyue, Ye, Xinyue, Duan, Lian, Peng, Qiong, Ye, Xinyue, Ye, Xinyue, Duan, Lian, and Peng, Qiong

Abstract

Spatiotemporal prediction of crime is crucial for public safety and smart cities operation. As crime incidents are distributed sparsely across space and time, existing deep-learning methods constrained by coarse spatial scale offer only limited values in prediction of crime density. This paper proposes the use of deep inception-residual networks (DIRNet) to conduct fine-grained, theft-related crime prediction based on non-emergency service request data (311 events). Specifically, it outlines the employment of inception units comprising asymmetrical convolution layers to draw low-level spatiotemporal dependencies hidden in crime events and complaint records in the 311 dataset. Afterward, this paper details how residual units can be applied to capture high-level spatiotemporal features from low-level spatiotemporal dependencies for the final prediction. The effectiveness of the proposed DIRNet is evaluated based on theft-related crime data and 311 data in New York City from 2010 to 2015. The results confirm that the DIRNet obtains an average F1 of 71%, which is better than other prediction models.

Published
2021

231. Developing Human-Centered Urban Digital Twins for Community Infrastructure Resilience: A Research Agenda.

Author

Ye, Xinyue, Du, Jiaxin, Han, Yu, Newman, Galen, Retchless, David, Zou, Lei, Ham, Youngjib, and Cai, Zhenhang

Subjects
*DIGITAL twins, *VIRTUAL communities, *URBAN landscape architecture, *TECHNOLOGICAL innovations, *URBAN planning, *COMMUNITIES
Abstract

Urban digital twins (UDTs) have been identified as a potential technology to achieve digital transformative positive urban change through landscape architecture and urban planning. However, how this new technology will influence community resilience and adaptation planning is currently unclear. This article: (1) offers a scoping review of existing studies constructing UDTs, (2) identifies challenges and opportunities of UDT technologies for community adaptation planning, and (3) develops a conceptual framework of UDTs for community infrastructure resilience. This article highlights the need for integrating multi-agent interactions, artificial intelligence, and coupled natural–physical–social systems into a human-centered UDTs framework to improve community infrastructure resilience. [ABSTRACT FROM AUTHOR]

Published
2023
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240. sj-docx-3-epb-10.1177_23998083211064624 ��� Supplemental Material for Analyze the usage of urban greenways through social media images and computer vision

Author

Song, Yang, Ning, Huan, Ye, Xinyue, Chandana, Divya, and Wang, Shaohua

Subjects
FOS: Social and economic geography, Geography, 120599 Urban and Regional Planning not elsewhere classified
Abstract

Supplemental Material, sj-docx-3-epb-10.1177_23998083211064624 for Analyze the usage of urban greenways through social media images and computer vision by Yang Song, Huan Ning, Xinyue Ye, Divya Chandana, Shaohua Wang in Environment and Planning B: Urban Analytics and City Science

Published
2022
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241. sj-pdf-1-epb-10.1177_23998083211064624 ��� Supplemental Material for Analyze the usage of urban greenways through social media images and computer vision

Author

Song, Yang, Ning, Huan, Ye, Xinyue, Chandana, Divya, and Wang, Shaohua

Subjects
FOS: Social and economic geography, Geography, 120599 Urban and Regional Planning not elsewhere classified
Abstract

Supplemental Material, sj-pdf-1-epb-10.1177_23998083211064624 for Analyze the usage of urban greenways through social media images and computer vision by Yang Song, Huan Ning, Xinyue Ye, Divya Chandana, Shaohua Wang in Environment and Planning B: Urban Analytics and City Science

Published
2022
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242. sj-pdf-2-epb-10.1177_23998083211064624 ��� Supplemental Material for Analyze the usage of urban greenways through social media images and computer vision

Author

Song, Yang, Ning, Huan, Ye, Xinyue, Chandana, Divya, and Wang, Shaohua

Subjects
FOS: Social and economic geography, Geography, 120599 Urban and Regional Planning not elsewhere classified
Abstract

Supplemental Material, sj-pdf-2-epb-10.1177_23998083211064624 for Analyze the usage of urban greenways through social media images and computer vision by Yang Song, Huan Ning, Xinyue Ye, Divya Chandana, Shaohua Wang in Environment and Planning B: Urban Analytics and City Science

Published
2022
Full Text
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