Research on the Efficiency of Bridge Crack Detection by Coupling Deep Learning Frameworks with Convolutional Neural Networks.

Ma, Kaifeng; Meng, Xiang; Hao, Mengshu; Huang, Guiping; Hu, Qingfeng; He, Peipei

Ma, Kaifeng; Meng, Xiang; Hao, Mengshu; Huang, Guiping; Hu, Qingfeng; He, Peipei.

Afiliação

Ma K; College of Surveying and Geo-Informatics, North China University of Water Resources and Electric Power, Zhengzhou 450046, China.
Meng X; College of Surveying and Geo-Informatics, North China University of Water Resources and Electric Power, Zhengzhou 450046, China.
Hao M; College of Surveying and Geo-Informatics, North China University of Water Resources and Electric Power, Zhengzhou 450046, China.
Huang G; College of Surveying and Geo-Informatics, North China University of Water Resources and Electric Power, Zhengzhou 450046, China.
Hu Q; College of Surveying and Geo-Informatics, North China University of Water Resources and Electric Power, Zhengzhou 450046, China.
He P; College of Surveying and Geo-Informatics, North China University of Water Resources and Electric Power, Zhengzhou 450046, China.

Sensors (Basel) ; 23(16)2023 Aug 19.

Article em En | MEDLINE | ID: mdl-37631807

Palavras-chave

DLF; bridge crack detection; evaluation indicators; object detection model; semantic segmentation model

Texto completo

Imprimir

XML

PubMed Links

Buscar no Google

Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Diagnostic_studies Idioma: En Revista: Sensors (Basel) Ano de publicação: 2023 Tipo de documento: Article País de afiliação: China

Texto completo

Imprimir

XML

PubMed Links

Buscar no Google