Bibliometric analysis and review of deep learning-based crack detection literature published between 2010 and 2022
The use of deep learning (DL) in civil inspection, especially in crack detection, has
increased over the past years to ensure long-term structural safety and integrity. To achieve …
increased over the past years to ensure long-term structural safety and integrity. To achieve …
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 …
Applications of computer vision-based structural health monitoring and condition assessment in future smart cities
TG Mondal, MR Jahanshahi - The rise of smart cities, 2022 - Elsevier
It is generally accepted that artificial intelligence (AI)-enabled computer vision will drive the
next revolution in information modeling and decision-making actualizing the vision of future …
next revolution in information modeling and decision-making actualizing the vision of future …
Automated visual inspection of fabric image using deep learning approach for defect detection
V Voronin, R Sizyakin, M Zhdanova… - … and Machine Vision …, 2021 - spiedigitallibrary.org
As a popular topic in automation, fabric defect detection is a necessary and essential step of
quality control in the textile manufacturing industry. The main challenge for automatically …
quality control in the textile manufacturing industry. The main challenge for automatically …
[HTML][HTML] Crack45K: integration of vision transformer with tubularity flow field (TuFF) and sliding-window approach for crack-segmentation in pavement structures
Recently, deep-learning (DL)-based crack-detection systems have proven to be the method
of choice for image processing-based inspection systems. However, human-like …
of choice for image processing-based inspection systems. However, human-like …
A deep and multiscale network for pavement crack detection based on function-specific modules
Using 3D asphalt pavement surface data, a deep and multiscale network named CrackNet-
M is proposed in this paper for pixel-level crack detection for improvements in both accuracy …
M is proposed in this paper for pixel-level crack detection for improvements in both accuracy …
Automatic assessment of roofs conditions using artificial intelligence (AI) and unmanned aerial vehicles (UAVs)
Building roof inspections must be performed regularly to ensure repairs and replacements
are done promptly. These inspections get overlooked on sloped roofs due to the inefficiency …
are done promptly. These inspections get overlooked on sloped roofs due to the inefficiency …
Dense Multiscale Feature Learning Transformer Embedding Cross-Shaped Attention for Road Damage Detection
Road damage detection is essential to the maintenance and management of roads. The
morphological road damage contains a large number of multi-scale features, which means …
morphological road damage contains a large number of multi-scale features, which means …
LCSNet: Light-Weighted Convolution-Based Segmentation Method with Separable Multi-Directional Convolution Module for Concrete Crack Segmentation in Drones
X Zhang, H Huang - Electronics, 2024 - mdpi.com
Concrete cracks pose significant safety hazards to buildings, and semantic segmentation
models based on deep learning have achieved state-of-the-art results in concrete crack …
models based on deep learning have achieved state-of-the-art results in concrete crack …
Virtual restoration of paintings based on deep learning
R Sizyakin, V Voronin… - … Conference on Machine …, 2022 - spiedigitallibrary.org
Over time, crack pattern (craquelure) inevitably develops in paintings as a sign of their
ageing, sometimes accompanied by larger losses of paint (lacunas). In restoration …
ageing, sometimes accompanied by larger losses of paint (lacunas). In restoration …