Assessment of Convolutional Neural Network Pre-Trained Models for Detection and Orientation of Cracks.

Qayyum, Waqas; Ehtisham, Rana; Bahrami, Alireza; Camp, Charles; Mir, Junaid; Ahmad, Afaq

Qayyum, Waqas; Ehtisham, Rana; Bahrami, Alireza; Camp, Charles; Mir, Junaid; Ahmad, Afaq.

Afiliação

Qayyum W; Department of Civil Engineering, University of Engineering and Technology, Taxila, Rawalpindi 46600, Pakistan.
Ehtisham R; Department of Civil Engineering, University of Engineering and Technology, Taxila, Rawalpindi 46600, Pakistan.
Bahrami A; Department of Building Engineering, Energy Systems, and Sustainability Science, Faculty of Engineering and Sustainable Development, University of Gävle, 801 76 Gävle, Sweden.
Camp C; Department of Civil Engineering, University of Memphis, Memphis, TN 38152, USA.
Mir J; Department of Electrical Engineering, University of Engineering and Technology, Taxila, Rawalpindi 46600, Pakistan.
Ahmad A; Department of Civil Engineering, University of Engineering and Technology, Taxila, Rawalpindi 46600, Pakistan.

Materials (Basel) ; 16(2)2023 Jan 14.

Article em En | MEDLINE | ID: mdl-36676563

Palavras-chave

convolutional neural networks; cracks detection; deep learning; orientation of cracks; pre-trained models

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Diagnostic_studies Idioma: En Revista: Materials (Basel) Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Paquistão

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