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Creating A Coefficient of Change in the Built Environment After a Natural Disaster
The study utilizes the algorithm Seg-Net to perform semantic segmentation of the built environment from the satellite images in both instances (prior and post-natural disasters).
A Machine learning approach for rapid disaster response based on multi-modal data. The case of housing & shelter needs
To address this gap and make a headway in comprehensive assessments, this paper proposes a machine learning workflow that aims to fuse and rapidly analyse multimodal data.
Indexical Cities: Articulating Personal Models of Urban Preference with Geotagged Data
How to assess the potential of liking a city or a neighborhood before ever having been there.
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