Data-driven structural health monitoring and damage detection through deep learning: State-of-the-art review
Data-driven methods in structural health monitoring (SHM) is gaining popularity due to
recent technological advancements in sensors, as well as high-speed internet and cloud …
recent technological advancements in sensors, as well as high-speed internet and cloud …
Machine learning applied to the design and inspection of reinforced concrete bridges: Resilient methods and emerging applications
Abstract Machine learning is one of the key pillars of industry 4.0 that has enabled rapid
technological advancement through establishing complex connections among …
technological advancement through establishing complex connections among …
Vision transformer-based autonomous crack detection on asphalt and concrete surfaces
Previous research has shown the high accuracy of convolutional neural networks (CNNs) in
asphalt and concrete crack detection in controlled conditions. Yet, human-like generalisation …
asphalt and concrete crack detection in controlled conditions. Yet, human-like generalisation …
Tiny‐Crack‐Net: A multiscale feature fusion network with attention mechanisms for segmentation of tiny cracks
Convolutional neural networks (CNNs) have gained growing interest in recent years for their
advantages in detecting cracks on concrete bridge components. Class imbalance is a …
advantages in detecting cracks on concrete bridge components. Class imbalance is a …
Automatic detection of sewer defects based on improved you only look once algorithm
The drainage system is an important part of civil infrastructure. However, the underground
sewage pipe will gradually suffer from defects over time, such as tree roots, deposits …
sewage pipe will gradually suffer from defects over time, such as tree roots, deposits …
Detection of cervical cancer cells in whole slide images using deformable and global context aware faster RCNN-FPN
X Li, Z Xu, X Shen, Y Zhou, B **ao, TQ Li - Current Oncology, 2021 - mdpi.com
Cervical cancer is a worldwide public health problem with a high rate of illness and mortality
among women. In this study, we proposed a novel framework based on Faster RCNN-FPN …
among women. In this study, we proposed a novel framework based on Faster RCNN-FPN …
Concrete cracks detection using convolutional neuralnetwork based on transfer learning
C Su, W Wang - Mathematical Problems in Engineering, 2020 - Wiley Online Library
Crack plays a critical role in the field of evaluating the quality of concrete structures, which
affects the safety, applicability, and durability of the structure. Due to its excellent …
affects the safety, applicability, and durability of the structure. Due to its excellent …
A sigmoid‐optimized encoder–decoder network for crack segmentation with copy‐edit‐paste transfer learning
The automatic recognition of cracks is an essential requirement for the cost‐efficient
maintenance of concrete structures, such as bridges, buildings, and roads. It should allow …
maintenance of concrete structures, such as bridges, buildings, and roads. It should allow …
Automated bridge crack evaluation through deep super resolution network-based hybrid image matching
This article proposes a deep super resolution crack network (SrcNet)-based automated
bridge crack evaluation technique through hybrid image matching. The hybrid images …
bridge crack evaluation technique through hybrid image matching. The hybrid images …
[PDF][PDF] 人工神经网络模型发展及应用综述
张驰， 郭媛， 黎明 - 计算机工程与应用, 2021 - mool.njfu.edu.cn
人工神经网络与其他学科领域联系日益紧密, 人们通过对人工神经网络层结构的探索和改进来
解决各个领域的问题. 根据人工神经网络相关文献进行分析, 综述了人工神经网络算法以及网络 …
解决各个领域的问题. 根据人工神经网络相关文献进行分析, 综述了人工神经网络算法以及网络 …