A review on machine learning styles in computer vision—techniques and future directions
Computer applications have considerably shifted from single data processing to machine
learning in recent years due to the accessibility and availability of massive volumes of data …
learning in recent years due to the accessibility and availability of massive volumes of data …
Deep learning-based road damage detection and classification for multiple countries
Many municipalities and road authorities seek to implement automated evaluation of road
damage. However, they often lack technology, know-how, and funds to afford state-of-the-art …
damage. However, they often lack technology, know-how, and funds to afford state-of-the-art …
Automated road defect and anomaly detection for traffic safety: a systematic review
Recently, there has been a substantial increase in the development of sensor technology.
As enabling factors, computer vision (CV) combined with sensor technology have made …
As enabling factors, computer vision (CV) combined with sensor technology have made …
[HTML][HTML] YOLOv5s-M: A deep learning network model for road pavement damage detection from urban street-view imagery
M Ren, X Zhang, X Chen, B Zhou, Z Feng - International Journal of Applied …, 2023 - Elsevier
Road pavement damage affects driving comfort markedly, threatens driving safety, and may
even cause traffic accidents. The traffic management department conventionally captures …
even cause traffic accidents. The traffic management department conventionally captures …
Global road damage detection: State-of-the-art solutions
This paper summarizes the Global Road Damage Detection Challenge (GRDDC), a Big
Data Cup organized as a part of the IEEE International Conference on Big Data'2020. The …
Data Cup organized as a part of the IEEE International Conference on Big Data'2020. The …
[HTML][HTML] Automatic tunnel lining crack detection via deep learning with generative adversarial network-based data augmentation
Z Zhou, J Zhang, C Gong, W Wu - Underground Space, 2023 - Elsevier
Aiming at solving the challenges of insufficient data samples and low detection efficiency in
tunnel lining crack detection methods based on deep learning, a novel detection approach …
tunnel lining crack detection methods based on deep learning, a novel detection approach …
An improved YOLOv5 crack detection method combined with transformer
X **ang, Z Wang, Y Qiao - IEEE Sensors Journal, 2022 - ieeexplore.ieee.org
Efficient detection of pavement cracks can effectively prevent traffic accidents and reduce
pavement maintenance costs. In order to overcome the complicated and uneconomical …
pavement maintenance costs. In order to overcome the complicated and uneconomical …
Ensemble multifeatured deep learning models and applications: A survey
Ensemble multifeatured deep learning methodology has emerged as a powerful approach
to overcome the limitations of single deep learning models in terms of generalization …
to overcome the limitations of single deep learning models in terms of generalization …
Human behavior in image-based Road Health Inspection Systems despite the emerging AutoML
T Siriborvornratanakul - Journal of Big Data, 2022 - Springer
Introduction The emergence of automated machine learning or AutoML has raised an
interesting trend of no-code and low-code machine learning where most tasks in the …
interesting trend of no-code and low-code machine learning where most tasks in the …
Real-time pavement damage detection with damage shape adaptation
Intelligent detection of pavement damage is crucial to road maintenance. Timely
identification of cracks and potholes helps prolong the road service life. Current detection …
identification of cracks and potholes helps prolong the road service life. Current detection …