Structural crack detection using deep convolutional neural networks
Abstract Convolutional Neural Networks (CNN) have immense potential to solve a broad
range of computer vision problems. It has achieved encouraging results in numerous …
range of computer vision problems. It has achieved encouraging results in numerous …
Image based techniques for crack detection, classification and quantification in asphalt pavement: a review
Pavement condition information is a significant component in Pavement Management
Systems. The labeling and quantification of the type, severity, and extent of surface cracking …
Systems. The labeling and quantification of the type, severity, and extent of surface cracking …
DenseSPH-YOLOv5: An automated damage detection model based on DenseNet and Swin-Transformer prediction head-enabled YOLOv5 with attention mechanism
Objective. Computer vision-based up-to-date accurate damage classification and
localization are of decisive importance for infrastructure monitoring, safety, and the …
localization are of decisive importance for infrastructure monitoring, safety, and the …
Feature pyramid and hierarchical boosting network for pavement crack detection
Pavement crack detection is a critical task for insuring road safety. Manual crack detection is
extremely time-consuming. Therefore, an automatic road crack detection method is required …
extremely time-consuming. Therefore, an automatic road crack detection method is required …
Road crack detection using deep convolutional neural network
Automatic detection of pavement cracks is an important task in transportation maintenance
for driving safety assurance. However, it remains a challenging task due to the intensity …
for driving safety assurance. However, it remains a challenging task due to the intensity …
Pavement distress detection and classification based on YOLO network
The detection and classification of pavement distress (PD) play a critical role in pavement
maintenance and rehabilitation. Research on PD automation detection and measurement …
maintenance and rehabilitation. Research on PD automation detection and measurement …
How to get pavement distress detection ready for deep learning? A systematic approach
Road condition acquisition and assessment are the key to guarantee their permanent
availability. In order to maintain a country's whole road network, millions of high-resolution …
availability. In order to maintain a country's whole road network, millions of high-resolution …
Surface fatigue crack identification in steel box girder of bridges by a deep fusion convolutional neural network based on consumer-grade camera images
This study conducts crack identification from real-world images containing complicated
disturbance information (cracks, handwriting scripts, and background) inside steel box …
disturbance information (cracks, handwriting scripts, and background) inside steel box …
Road crack detection using deep convolutional neural network and adaptive thresholding
Crack is one of the most common road distresses which may pose road safety hazards.
Generally, crack detection is performed by either certified inspectors or structural engineers …
Generally, crack detection is performed by either certified inspectors or structural engineers …
Computer vision applications in intelligent transportation systems: a survey
As technology continues to develop, computer vision (CV) applications are becoming
increasingly widespread in the intelligent transportation systems (ITS) context. These …
increasingly widespread in the intelligent transportation systems (ITS) context. These …