Deep convolutional neural network for weld defect classification in radiographic images
The quality of welds is critical to the safety of structures in construction, so early detection of irregularities is crucial. Advances in machine vision inspection technologies, such as deep learning models, have improved the detection of weld defects. This paper presents a new CNN model based on R...
- Autores:
-
Palma Ramírez, Dayana
Ross Veitía, Bárbara D.
Font Ariosa, Pablo
Espinel Hernández, Alejandro
Sánchez Roca, Ángel
Carvajar Fals, Hipólito
Nuñez Álvarez, José R.
Hernández Herrera, Hernan
- Tipo de recurso:
- Article of investigation
- Fecha de publicación:
- 2024
- Institución:
- Corporación Universidad de la Costa
- Repositorio:
- REDICUC - Repositorio CUC
- Idioma:
- eng
- OAI Identifier:
- oai:repositorio.cuc.edu.co:11323/13481
- Acceso en línea:
- https://hdl.handle.net/11323/13481
https://repositorio.cuc.edu.co/
- Palabra clave:
- Radiographic testing
Classification
Weld defects
CNNs
Transfer learning
- Rights
- openAccess
- License
- Atribución 4.0 Internacional (CC BY 4.0)