Recent advances and applications of deep learning methods in materials science
Deep learning (DL) is one of the fastest-growing topics in materials data science, with
rapidly emerging applications spanning atomistic, image-based, spectral, and textual data …
rapidly emerging applications spanning atomistic, image-based, spectral, and textual data …
Machine learning in concrete science: applications, challenges, and best practices
Concrete, as the most widely used construction material, is inextricably connected with
human development. Despite conceptual and methodological progress in concrete science …
human development. Despite conceptual and methodological progress in concrete science …
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 …
A critical review and comparative study on image segmentation-based techniques for pavement crack detection
N Kheradmandi, V Mehranfar - Construction and Building Materials, 2022 - Elsevier
The prompt detection of early decay in the pavement could be an auspicious technique in
road maintenance. Admittedly, early crack detection allows preventive measures to be taken …
road maintenance. Admittedly, early crack detection allows preventive measures to be taken …
Edge AI‐Based Automated Detection and Classification of Road Anomalies in VANET Using Deep Learning
Road surface defects are crucial problems for safe and smooth traffic flow. Due to climate
changes, low quality of construction material, large flow of traffic, and heavy vehicles, road …
changes, low quality of construction material, large flow of traffic, and heavy vehicles, road …
Computer vision framework for crack detection of civil infrastructure—A review
Civil infrastructure (eg, buildings, roads, underground tunnels) could lose its expected
physical and functional conditions after years of operation. Timely and accurate inspection …
physical and functional conditions after years of operation. Timely and accurate inspection …
A review of computer vision–based structural health monitoring at local and global levels
Structural health monitoring at local and global levels using computer vision technologies
has gained much attention in the structural health monitoring community in research and …
has gained much attention in the structural health monitoring community in research and …
A decade survey of transfer learning (2010–2020)
Transfer learning (TL) has been successfully applied to many real-world problems that
traditional machine learning (ML) cannot handle, such as image processing, speech …
traditional machine learning (ML) cannot handle, such as image processing, speech …
A comprehensive survey on transfer learning
Transfer learning aims at improving the performance of target learners on target domains by
transferring the knowledge contained in different but related source domains. In this way, the …
transferring the knowledge contained in different but related source domains. In this way, the …
A systematic review of convolutional neural network-based structural condition assessment techniques
With recent advances in non-contact sensing technology such as cameras, unmanned aerial
and ground vehicles, the structural health monitoring (SHM) community has witnessed a …
and ground vehicles, the structural health monitoring (SHM) community has witnessed a …