相关参考文献
注意：仅列出部分参考文献，下载原文获取全部文献信息。
Article
Engineering, Multidisciplinary
Tan N. Nguyen et al.
Summary: This paper proposes a one-iteration nonlinear solver (OINS) for solving nonlinear problems in solid mechanics. By using time series prediction and the modified Riks method, OINS eliminates the need for numerous iterations and computations required by existing iterative algorithms. Through numerical investigations, it is shown that OINS is powerful, highly accurate, and significantly reduces the number of iterations and computational complexity compared to conventional methods.
INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN ENGINEERING
(2022)
Article
Engineering, Multidisciplinary
Yanfen Li et al.
Summary: This paper introduces an automatic instance segmentation-based defect analysis framework, which addresses the issues of blurriness and vaporous environment in traditional sewer defect inspection approaches. It presents a novel defect segmentation model and a publicly available dataset. Experimental results demonstrate a significant improvement in mean Average Precision.
Article
Construction & Building Technology
L. Minh Dang et al.
Summary: This study proposes an efficient and robust sewer defect localization framework, which achieves accurate defect detection and severity analysis. Experimental results demonstrate that the proposed system outperforms previous approaches in sewer defect detection.
CONSTRUCTION AND BUILDING MATERIALS
(2022)
Article
Construction & Building Technology
L. Minh Dang et al.
Summary: This research proposes a deep learning-based tunnel lining crack segmentation framework for automated detection and measurement of cracks. The experimental results demonstrate that the framework performs well.
TUNNELLING AND UNDERGROUND SPACE TECHNOLOGY
(2022)
Article
Mathematics
Tan N Nguyen et al.
Summary: This paper aims to improve the load-carrying capacity and strength of membrane structures by utilizing functionally graded carbon-nanotube-reinforced composite material, investigating both reinforced and unreinforced membranes using a unified adaptive approach. The formulation takes into account membrane, shear, and bending strains/stiffnesses, and can be applied to various types of structures, showing high accuracy in verification studies. Additionally, the study explores the effects of CNTs distribution, volume fraction, thickness, curvature, radius-to-thickness, and length-to-radius ratios on the behavior of FG-CNTRC membranes.
Article
Construction & Building Technology
Saeed Talebi et al.
Summary: This research aims to develop a framework for digital visual inspections of masonry railway bridges using multiple NDT technologies to overcome the limitations of conventional inspection regimes. A digitally enhanced visual inspection framework is developed by using complementary optical methods, which require fewer subjective interpretations and can be conducted remotely, making it safer and more efficient compared to traditional methods.
CONSTRUCTION INNOVATION-ENGLAND
(2022)
Article
Construction & Building Technology
Dimitrios Loverdos et al.
Summary: This paper aims to improve automation in brick segmentation and crack detection of masonry walls through image-based techniques and machine learning. It shows that machine learning provides better outcomes than typical image-processing applications for brick segmentation and crack detection.
AUTOMATION IN CONSTRUCTION
(2022)
Article
Computer Science, Interdisciplinary Applications
Hanxiang Wang et al.
Summary: An innovative framework combining weakly supervised learning methods and fully supervised learning methods is proposed for crack detection and segmentation in tunnel images. The proposed method successfully judges the risk levels of detected cracks and performs calculations on different types of cracks. Furthermore, the framework achieves comparable performance to manual annotation-based frameworks, showcasing the effectiveness of weakly supervised learning methods in accurately labeling images.
COMPUTERS IN INDUSTRY
(2021)
Article
Construction & Building Technology
Dimitris Dais et al.
Summary: This study explores deep learning techniques for crack detection on masonry walls, achieving an accuracy of 95.3%. Leveraging transfer learning, crack segmentation on masonry surfaces at the pixel level was successfully implemented. This represents the first application of deep learning for pixel-level crack segmentation on masonry surfaces.
AUTOMATION IN CONSTRUCTION
(2021)
Article
Construction & Building Technology
C. Scuro et al.
Summary: The main goal of using the IoT paradigm is to extend the connectivity of various common SHM devices through the Internet, allowing for data transmission and processing and creating new scenarios for acquisition systems in different fields of science and engineering. Innovations have led researchers to apply the IoT paradigm to SHM of masonry structures, ensuring successful experimental results and promising future improvements.
CONSTRUCTION AND BUILDING MATERIALS
(2021)
Article
Chemistry, Analytical
Mitchell J. Hallee et al.
Summary: The study focused on crack detection in masonry using various machine learning methods, with the CNN showing better performance in domain adaptation from lab to real-world images compared to simple classifiers. Conversely, the simple classifiers performed significantly better in the reverse domain adaptation task.
Proceedings Paper
Engineering, Mechanical
Nicola Cavalagli et al.
ART COLLECTIONS 2020, SAFETY ISSUE (ARCO 2020, SAFETY)
(2020)
Article
Computer Science, Interdisciplinary Applications
Allen Zhang et al.
COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING
(2019)
Article
Computer Science, Artificial Intelligence
Qin Zou et al.
IEEE TRANSACTIONS ON IMAGE PROCESSING
(2019)
Article
Construction & Building Technology
Enrique Valero et al.
AUTOMATION IN CONSTRUCTION
(2019)
Article
Computer Science, Interdisciplinary Applications
Xincong Yang et al.
COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING
(2018)
Article
Engineering, Manufacturing
Max Ferguson et al.
SMART AND SUSTAINABLE MANUFACTURING SYSTEMS
(2018)
Article
Computer Science, Interdisciplinary Applications
Shi Qiu et al.
JOURNAL OF COMPUTING IN CIVIL ENGINEERING
(2017)
Proceedings Paper
Computer Science, Artificial Intelligence
Kaiming He et al.
2017 IEEE INTERNATIONAL CONFERENCE ON COMPUTER VISION (ICCV)
(2017)
Article
Computer Science, Artificial Intelligence
Romain Marie et al.
PATTERN RECOGNITION
(2016)
