Cargando…
Vision-Based Autonomous Crack Detection of Concrete Structures Using a Fully Convolutional Encoder–Decoder Network
The visual inspection of massive civil infrastructure is a common trend for maintaining its reliability and structural health. However, this procedure, which uses human inspectors, requires long inspection times and relies on the subjective and empirical knowledge of the inspectors. To address these...
Autores principales: | Islam, M. M. Manjurul, Kim, Jong-Myon |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6806320/ https://www.ncbi.nlm.nih.gov/pubmed/31574963 http://dx.doi.org/10.3390/s19194251 |
Ejemplares similares
-
Crack Classification of a Pressure Vessel Using Feature Selection and Deep Learning Methods
por: Islam, Manjurul, et al.
Publicado: (2018) -
Learning Semantic Graphics Using Convolutional Encoder–Decoder Network for Autonomous Weeding in Paddy
por: Adhikari, Shyam Prasad, et al.
Publicado: (2019) -
TISNet-Enhanced Fully Convolutional Network with Encoder-Decoder Structure for Tongue Image Segmentation in Traditional Chinese Medicine
por: Huang, Xiaodong, et al.
Publicado: (2020) -
Automatic Crack Detection on Road Pavements Using Encoder-Decoder Architecture
por: Fan, Zhun, et al.
Publicado: (2020) -
Learning to Detect Cracks on Damaged Concrete Surfaces Using Two-Branched Convolutional Neural Network
por: Lee, Jieun, et al.
Publicado: (2019)