Cargando…
Enhanced Intelligent Identification of Concrete Cracks Using Multi-Layered Image Preprocessing-Aided Convolutional Neural Networks
Crack identification plays an essential role in the health diagnosis of various concrete structures. Among different intelligent algorithms, the convolutional neural networks (CNNs) has been demonstrated as a promising tool capable of efficiently identifying the existence and evolution of concrete c...
Autores principales: | Fu, Ronghua, Xu, Hao, Wang, Zijian, Shen, Lei, Cao, Maosen, Liu, Tongwei, Novák, Drahomír |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7181115/ https://www.ncbi.nlm.nih.gov/pubmed/32260302 http://dx.doi.org/10.3390/s20072021 |
Ejemplares similares
-
Learning to Detect Cracks on Damaged Concrete Surfaces Using Two-Branched Convolutional Neural Network
por: Lee, Jieun, et al.
Publicado: (2019) -
A Data-Driven Damage Identification Framework Based on Transmissibility Function Datasets and One-Dimensional Convolutional Neural Networks: Verification on a Structural Health Monitoring Benchmark Structure
por: Liu, Tongwei, et al.
Publicado: (2020) -
SDNET2018: An annotated image dataset for non-contact concrete crack detection using deep convolutional neural networks
por: Dorafshan, Sattar, et al.
Publicado: (2018) -
Automatic Detection of Cracks in Cracked Tooth Based on Binary Classification Convolutional Neural Networks
por: Guo, Juncheng, et al.
Publicado: (2022) -
Concrete Protective Layer Cracking Caused by Non-Uniform Corrosion of Reinforcements
por: Zhang, Lu, et al.
Publicado: (2019)