Cargando…
A Hybrid Crack Detection Approach for Scanning Electron Microscope Image Using Deep Learning Method
The scanning electron microscope (SEM) is widely used in the analysis and research of materials, including fracture analysis, microstructure morphology, and nanomaterial analysis. With the rapid development of materials science and computer vision technology, the level of detection technology is con...
Autores principales: | Zhao, Lun, Pan, Yunlong, Wang, Sen, Zhang, Liang, Islam, Md Shafiqul |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8371647/ https://www.ncbi.nlm.nih.gov/pubmed/34471443 http://dx.doi.org/10.1155/2021/5558668 |
Ejemplares similares
-
Classification of scanning electron microscope images of pharmaceutical excipients using deep convolutional neural networks with transfer learning
por: Iwata, Hiroaki, et al.
Publicado: (2022) -
Crack detection for concrete bridges with imaged based deep learning
por: Wan, Chunfeng, et al.
Publicado: (2022) -
Non-destructive monitoring of forming quality of self-piercing riveting via a lightweight deep learning
por: Lin, Sen, et al.
Publicado: (2023) -
Tunnel Crack Detection Method and Crack Image Processing Algorithm Based on Improved Retinex and Deep Learning
por: Wu, Jie, et al.
Publicado: (2023) -
Research on tire crack detection using image deep learning method
por: Lin, Shih-Lin
Publicado: (2023)