Classification of Building Damage Using a Novel Convolutional Neural Network Based on Post-Disaster Aerial Images

The accurate and timely identification of the degree of building damage is critical for disaster emergency response and loss assessment. Although many methods have been proposed, most of them divide damaged buildings into two categories—intact and damaged—which is insufficient to meet practical need...

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Detalles Bibliográficos
Autores principales: Hong, Zhonghua, Zhong, Hongzheng, Pan, Haiyan, Liu, Jun, Zhou, Ruyan, Zhang, Yun, Han, Yanling, Wang, Jing, Yang, Shuhu, Zhong, Changyue
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9371387/
https://www.ncbi.nlm.nih.gov/pubmed/35957476
http://dx.doi.org/10.3390/s22155920

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9371387/
https://www.ncbi.nlm.nih.gov/pubmed/35957476
http://dx.doi.org/10.3390/s22155920

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