Eyes on the Streets: Leveraging Street-Level Imaging to Model Urban Crime Dynamics
Fuente:
arXiv
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| Autores principales: | , , |
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| Formato: | Preprint |
| Publicado: |
2024
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| Materias: | |
| Acceso en línea: | |
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| _version_ | 1866913320767848448 |
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| author | Qi, Zhixuan Luo, Huaiying Chi, Chen |
| author_facet | Qi, Zhixuan Luo, Huaiying Chi, Chen |
| contents | This study addresses the challenge of urban safety in New York City by examining the relationship between the built environment and crime rates using machine learning and a comprehensive dataset of street view images. We aim to identify how urban landscapes correlate with crime statistics, focusing on the characteristics of street views and their association with crime rates. The findings offer insights for urban planning and crime prevention, highlighting the potential of environmental design in enhancing public safety. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2404_10147 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Eyes on the Streets: Leveraging Street-Level Imaging to Model Urban Crime Dynamics Qi, Zhixuan Luo, Huaiying Chi, Chen Computer Vision and Pattern Recognition This study addresses the challenge of urban safety in New York City by examining the relationship between the built environment and crime rates using machine learning and a comprehensive dataset of street view images. We aim to identify how urban landscapes correlate with crime statistics, focusing on the characteristics of street views and their association with crime rates. The findings offer insights for urban planning and crime prevention, highlighting the potential of environmental design in enhancing public safety. |
| title | Eyes on the Streets: Leveraging Street-Level Imaging to Model Urban Crime Dynamics |
| topic | Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2404.10147 |