Rapid Post-Earthquake Structural Damage Assessment Using Convolutional Neural Networks and Transfer Learning

The adoption of artificial intelligence in post-earthquake inspections and reconnaissance has received considerable attention in recent years, owing to its exponential increase in computation capabilities and inherent potential in addressing disadvantages associated with manual inspections. Herein,...

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Detalles Bibliográficos
Autores principales: Ogunjinmi, Peter Damilola, Park, Sung-Sik, Kim, Bubryur, Lee, Dong-Eun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9099597/
https://www.ncbi.nlm.nih.gov/pubmed/35591163
http://dx.doi.org/10.3390/s22093471

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9099597/
https://www.ncbi.nlm.nih.gov/pubmed/35591163
http://dx.doi.org/10.3390/s22093471

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