Automatic Detection and Identification of Defects by Deep Learning Algorithms from Pulsed Thermography Data.

Fang, Qiang; Ibarra-Castanedo, Clemente; Garrido, Iván; Duan, Yuxia; Maldague, Xavier

Fang, Qiang; Ibarra-Castanedo, Clemente; Garrido, Iván; Duan, Yuxia; Maldague, Xavier.

Afiliación

Fang Q; Computer Vision and Systems Laboratory, Department of Electrical and Computer Engineering, Université Laval, 1065, av. de la Médecine, Québec, QC G1V 0A6, Canada.
Ibarra-Castanedo C; Computer Vision and Systems Laboratory, Department of Electrical and Computer Engineering, Université Laval, 1065, av. de la Médecine, Québec, QC G1V 0A6, Canada.
Garrido I; GeoTECH Group, Department of Natural Resources and Environmental Engineering, CINTECX, Universidade de Vigo, Campus Universitario de Vigo, 36310 Vigo, Spain.
Duan Y; School of Physics and Electronics, Central South University, 932 Lushan South Road, Changsha 410083, China.
Maldague X; Computer Vision and Systems Laboratory, Department of Electrical and Computer Engineering, Université Laval, 1065, av. de la Médecine, Québec, QC G1V 0A6, Canada.

Sensors (Basel) ; 23(9)2023 May 01.

Article en En | MEDLINE | ID: mdl-37177648

Palabras clave

automatic defect identification and segmentation; convolutional neural network; deep-learning non-destructive evaluation (NDE); infrared image processing; infrared thermography; pulsed thermography

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Diagnostic_studies Idioma: En Revista: Sensors (Basel) Año: 2023 Tipo del documento: Article País de afiliación: Canadá Pais de publicación: Suiza

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