[HTML][HTML] Artificial intelligence and smart vision for building and construction 4.0: Machine and deep learning methods and applications

SK Baduge, S Thilakarathna, JS Perera… - Automation in …, 2022 - Elsevier
This article presents a state-of-the-art review of the applications of Artificial Intelligence (AI),
Machine Learning (ML), and Deep Learning (DL) in building and construction industry 4.0 in …

Deep learning-based pedestrian detection in autonomous vehicles: Substantial issues and challenges

S Iftikhar, Z Zhang, M Asim, A Muthanna… - Electronics, 2022 - mdpi.com
In recent years, autonomous vehicles have become more and more popular due to their
broad influence over society, as they increase passenger safety and convenience, lower fuel …

Surface crack detection using deep learning with shallow CNN architecture for enhanced computation

B Kim, N Yuvaraj, KR Sri Preethaa… - Neural Computing and …, 2021 - Springer
Surface cracks on the concrete structures are a key indicator of structural safety and
degradation. To ensure the structural health and reliability of the buildings, frequent structure …

Investigation of steel frame damage based on computer vision and deep learning

B Kim, N Yuvaraj, HW Park, KRS Preethaa… - Automation in …, 2021 - Elsevier
Visual damage inspection of steel frames by eyes alone is time-consuming and
cumbersome; therefore, it produces inconsistent results. Existing computer vision-based …

Multimodal pedestrian detection using metaheuristics with deep convolutional neural network in crowded scenes

DK Jain, X Zhao, G González-Almagro, C Gan… - Information …, 2023 - Elsevier
Pedestrian detection (PD) is a vital computer vision (CV) problem that is highly employed in
several real-time applications, namely autonomous driving methods, robotics, and security …

Ensemble machine learning-based approach for predicting of FRP–concrete interfacial bonding

B Kim, DE Lee, G Hu, Y Natarajan, S Preethaa… - Mathematics, 2022 - mdpi.com
Developments in fiber-reinforced polymer (FRP) composite materials have created a huge
impact on civil engineering techniques. Bonding properties of FRP led to its wide usage with …

EAD-DNN: Early Alzheimer's disease prediction using deep neural networks

P Thangavel, Y Natarajan, KRS Preethaa - Biomedical Signal Processing …, 2023 - Elsevier
Early Alzheimer's disease (EAD) diagnosis enables individuals to take preventative actions
before irreversible brain damage occurs. Memory and thinking skills get worse in alzheimer …

Monitoring the green evolution of vernacular buildings based on deep learning and multi-temporal remote sensing images

B Wen, F Peng, Q Yang, T Lu, B Bai, S Wu, F Xu - Building Simulation, 2023 - Springer
The increasingly mature computer vision (CV) technology represented by convolutional
neural networks (CNN) and available high-resolution remote sensing images (HR-RSIs) …

Rapid post-earthquake structural damage assessment using convolutional neural networks and transfer learning

PD Ogunjinmi, SS Park, B Kim, DE Lee - Sensors, 2022 - mdpi.com
The adoption of artificial intelligence in post-earthquake inspections and reconnaissance
has received considerable attention in recent years, owing to its exponential increase in …

Robust and fair undersea target detection with automated underwater vehicles for biodiversity data collection

R Dinakaran, L Zhang, CT Li, A Bouridane, R Jiang - Remote Sensing, 2022 - mdpi.com
Undersea/subsea data collection via automated underwater vehicles (AUVs) plays an
important role for marine biodiversity research, while it is often much more challenging than …