[HTML][HTML] UAV-embedded sensors and deep learning for pathology identification in building façades: A review
The use of geotechnologies in the field of diagnostic engineering has become ever more
present in the identification of pathological manifestations in buildings. The implementation …
present in the identification of pathological manifestations in buildings. The implementation …
[HTML][HTML] Deep learning-based models for environmental management: Recognizing construction, renovation, and demolition waste in-the-wild
The construction industry generates a substantial volume of solid waste, often destinated for
landfills, causing significant environmental pollution. Waste recycling is decisive in …
landfills, causing significant environmental pollution. Waste recycling is decisive in …
Computing the characteristics of defects in wooden structures using image processing and CNN
Wood, a time-honored construction material prized for its exceptional properties, has been in
use for millennia. Its enduring popularity is attributed to its remarkable strength, aesthetic …
use for millennia. Its enduring popularity is attributed to its remarkable strength, aesthetic …
Recent advances in crack detection technologies for structures: a survey of 2022-2023 literature
H Kaveh, R Alhajj - Frontiers in Built Environment, 2024 - frontiersin.org
Introduction Cracks, as structural defects or fractures in materials like concrete, asphalt, and
metal, pose significant challenges to the stability and safety of various structures. Addressing …
metal, pose significant challenges to the stability and safety of various structures. Addressing …
[HTML][HTML] Evaluation and optimisation of pre-trained CNN models for asphalt pavement crack detection and classification
This study explored the performance of ten pre-trained CNN architectures in detecting and
classifying asphalt pavement cracks from images. A comparison of eight optimisation …
classifying asphalt pavement cracks from images. A comparison of eight optimisation …
[HTML][HTML] A Deep Learning Approach for Surface Crack Classification and Segmentation in Unmanned Aerial Vehicle Assisted Infrastructure Inspections
Surface crack detection is an integral part of infrastructure health surveys. This work
presents a transformative shift towards rapid and reliable data collection capabilities …
presents a transformative shift towards rapid and reliable data collection capabilities …
Assessment of deep learning models for cutaneous Leishmania parasite diagnosis using microscopic images
Cutaneous leishmaniasis (CL) is a common illness that causes skin lesions, principally
ulcerations, on exposed regions of the body. Although neglected tropical diseases (NTDs) …
ulcerations, on exposed regions of the body. Although neglected tropical diseases (NTDs) …
[HTML][HTML] Image-based techniques for initial and long-term characterization of crack kinematics in reinforced concrete structures
B Vincens, E Corres, A Muttoni - Engineering Structures, 2024 - Elsevier
In the recent years, Digital Image Correlation (DIC) was applied with very promising results
to monitor cracks in reinforced concrete structures. However, current DIC measurements …
to monitor cracks in reinforced concrete structures. However, current DIC measurements …
Multi-layers deep learning model with feature selection for automated detection and classification of highway pavement cracks
Purpose Cracks are prevalent signs of pavement distress found on highways globally. The
use of artificial intelligence (AI) and deep learning (DL) for crack detection is increasingly …
use of artificial intelligence (AI) and deep learning (DL) for crack detection is increasingly …
Contrastive self-supervised representation learning framework for metal surface defect detection
Automated detection of defects on metal surfaces is crucial for ensuring quality control.
However, the scarcity of labeled datasets for emerging target defects poses a significant …
However, the scarcity of labeled datasets for emerging target defects poses a significant …