Enhancement of multi-class structural defect recognition using generative adversarial network
Recently, in the building and infrastructure fields, studies on defect detection methods using
deep learning have been widely implemented. For robust automatic recognition of defects in …
deep learning have been widely implemented. For robust automatic recognition of defects in …
[HTML][HTML] Accelerating multi-class defect detection of building façades using knowledge distillation of DCNN-based model
This paper proposes a high-speed detection method for multi-class defects in residential
building façades. Automated deep learning-based defect detection systems have been …
building façades. Automated deep learning-based defect detection systems have been …
Balanced semisupervised generative adversarial network for damage assessment from low‐data imbalanced‐class regime
In recent years, applying deep learning (DL) to assess structural damages has gained
growing popularity in vision‐based structural health monitoring (SHM). However, both data …
growing popularity in vision‐based structural health monitoring (SHM). However, both data …
Data augmentation for deep-learning-based multiclass structural damage detection using limited information
The deterioration of infrastructure's health has become more predominant on a global scale
during the 21st century. Aging infrastructure as well as those structures damaged by natural …
during the 21st century. Aging infrastructure as well as those structures damaged by natural …
Self‐training approach for crack detection using synthesized crack images based on conditional generative adversarial network
S Shim - Computer‐Aided Civil and Infrastructure Engineering, 2024 - Wiley Online Library
Urban infrastructure plays a crucial role in determining the quality of life for citizens.
However, given the increasing number of aging infrastructures, regular inspections are …
However, given the increasing number of aging infrastructures, regular inspections are …
MultiDefectNet: Multi-class defect detection of building façade based on deep convolutional neural network
Defects in residential building façades affect the structural integrity of buildings and degrade
external appearances. Defects in a building façade are typically managed using manpower …
external appearances. Defects in a building façade are typically managed using manpower …
Evaluation-oriented façade defects detection using rule-based deep learning method
Visual evaluation of façade condition plays an important role to ensure the structural health
of the whole building. To automatically achieve visual evaluation of façade condition with …
of the whole building. To automatically achieve visual evaluation of façade condition with …
Multiclass damage detection in concrete structures using a transfer learning‐based generative adversarial networks
A large amount of the world's existing infrastructure is reaching the end of its service life,
requiring intervention in the form of structural rehabilitation or replacement. A critical aspect …
requiring intervention in the form of structural rehabilitation or replacement. A critical aspect …
Façade defects classification from imbalanced dataset using meta learning‐based convolutional neural network
Façade inspection is a regular but necessary maintenance task to ensure the safety,
functioning, and aesthetics of a building. Traditional visual identification of façade defects is …
functioning, and aesthetics of a building. Traditional visual identification of façade defects is …
A large‐scale dataset of buildings and construction sites
X Cheng, M Jia, J He - Computer‐Aided Civil and Infrastructure …, 2024 - Wiley Online Library
With the rapid development of deep learning and machine automation technology, as well
as workforce aging, increasing labor costs, and other issues, an increasing number of …
as workforce aging, increasing labor costs, and other issues, an increasing number of …