Advances in computer vision-based civil infrastructure inspection and monitoring
Computer vision techniques, in conjunction with acquisition through remote cameras and
unmanned aerial vehicles (UAVs), offer promising non-contact solutions to civil infrastructure …
unmanned aerial vehicles (UAVs), offer promising non-contact solutions to civil infrastructure …
BIM, machine learning and computer vision techniques in underground construction: Current status and future perspectives
The architecture, engineering and construction (AEC) industry is experiencing a
technological revolution driven by booming digitisation and automation. Advances in …
technological revolution driven by booming digitisation and automation. Advances in …
Comparison of deep convolutional neural networks and edge detectors for image-based crack detection in concrete
This paper compares the performance of common edge detectors and deep convolutional
neural networks (DCNN) for image-based crack detection in concrete structures. A dataset of …
neural networks (DCNN) for image-based crack detection in concrete structures. A dataset of …
Machine learning for crack detection: Review and model performance comparison
With the advancement of machine learning (ML) and deep learning (DL), there is a great
opportunity to enhance the development of automatic crack detection algorithms. In this …
opportunity to enhance the development of automatic crack detection algorithms. In this …
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 …
A research on an improved Unet-based concrete crack detection algorithm
L Zhang, J Shen, B Zhu - Structural Health Monitoring, 2021 - journals.sagepub.com
Crack is an important indicator for evaluating the damage level of concrete structures.
However, traditional crack detection algorithms have complex implementation and weak …
However, traditional crack detection algorithms have complex implementation and weak …
Deep learning for detecting building defects using convolutional neural networks
Clients are increasingly looking for fast and effective means to quickly and frequently survey
and communicate the condition of their buildings so that essential repairs and maintenance …
and communicate the condition of their buildings so that essential repairs and maintenance …
[HTML][HTML] SDNET2018: An annotated image dataset for non-contact concrete crack detection using deep convolutional neural networks
SDNET2018 is an annotated image dataset for training, validation, and benchmarking of
artificial intelligence based crack detection algorithms for concrete. SDNET2018 contains …
artificial intelligence based crack detection algorithms for concrete. SDNET2018 contains …
Classification and quantification of cracks in concrete structures using deep learning image-based techniques
Visual inspection has been the most widely used technique for monitoring concrete
structures in service. Inspectors visually evaluate defects based on experience, skill, and …
structures in service. Inspectors visually evaluate defects based on experience, skill, and …
[HTML][HTML] Real-time detection of cracks on concrete bridge decks using deep learning in the frequency domain
This paper presents a vision-based crack detection approach for concrete bridge decks
using an integrated one-dimensional convolutional neural network (1D-CNN) and long short …
using an integrated one-dimensional convolutional neural network (1D-CNN) and long short …