Cargando…
UAV-Driven Structural Crack Detection and Location Determination Using Convolutional Neural Networks
Structural cracks are a vital feature in evaluating the health of aging structures. Inspectors regularly monitor structures’ health using visual information because early detection of cracks on highly trafficked structures is critical for maintaining the public’s safety. In this work, a framework fo...
Autores principales: | Choi, Daegyun, Bell, William, Kim, Donghoon, Kim, Jichul |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8069420/ https://www.ncbi.nlm.nih.gov/pubmed/33918951 http://dx.doi.org/10.3390/s21082650 |
Ejemplares similares
-
Automatic Detection of Cracks in Cracked Tooth Based on Binary Classification Convolutional Neural Networks
por: Guo, Juncheng, et al.
Publicado: (2022) -
GPS Spoofing Detection Method for Small UAVs Using 1D Convolution Neural Network
por: Sung, Young-Hwa, et al.
Publicado: (2022) -
Convolutional neural network for earthquake detection and location
por: Perol, Thibaut, et al.
Publicado: (2018) -
Detection and Length Measurement of Cracks Captured in Low Definitions Using Convolutional Neural Networks
por: Kim, Jin-Young, et al.
Publicado: (2023) -
Learning to Detect Cracks on Damaged Concrete Surfaces Using Two-Branched Convolutional Neural Network
por: Lee, Jieun, et al.
Publicado: (2019)