Building Stock Classification Using Machine Learning: A Case Study for Oslo, Norway

This paper describes a new concept to automatically characterize building types in urban areas based on publicly available image databases, making parts of seismic risk assessment more time and cost-effective, and improving the reliability of seismic risk assessment, especially in regions where buil...

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Bibliographic Details
Main Authors: Federica Ghione, Steffen Mæland, Abdelghani Meslem, Volker Oye
Format: Article
Language:English
Published: Frontiers Media S.A. 2022-06-01
Series:Frontiers in Earth Science
Subjects:
Online Access:https://www.frontiersin.org/articles/10.3389/feart.2022.886145/full