[HTML][HTML] A systematic review of data fusion techniques for optimized structural health monitoring
Advancements in structural health monitoring (SHM) techniques have spiked in the past few
decades due to the rapid evolution of novel sensing and data transfer technologies. This …
decades due to the rapid evolution of novel sensing and data transfer technologies. This …
A systematic review of optimization algorithms for structural health monitoring and optimal sensor placement
S Hassani, U Dackermann - Sensors, 2023 - mdpi.com
In recent decades, structural health monitoring (SHM) has gained increased importance for
ensuring the sustainability and serviceability of large and complex structures. To design an …
ensuring the sustainability and serviceability of large and complex structures. To design an …
Corrosion and coating defect assessment of coal handling and preparation plants (CHPP) using an ensemble of deep convolutional neural networks and decision …
In view of the problems of ineffective feature extraction and low detection accuracy in
existing detection system, this study presents a novel machine vision-based approach …
existing detection system, this study presents a novel machine vision-based approach …
[HTML][HTML] Compressive strength evaluation of cement-based materials in sulphate environment using optimized deep learning technology
Strength serves as a vital performance metric for assessing long-term durability of cement-
based materials. Nevertheless, there is a scarcity of models available for predicting residual …
based materials. Nevertheless, there is a scarcity of models available for predicting residual …
A real-time traffic sign recognition method using a new attention-based deep convolutional neural network for smart vehicles
Artificial Intelligence (AI) in the automotive industry allows car manufacturers to produce
intelligent and autonomous vehicles through the integration of AI-powered Advanced Driver …
intelligent and autonomous vehicles through the integration of AI-powered Advanced Driver …
Mutual coupling reduction in antenna arrays using artificial intelligence approach and inverse neural network surrogates
This paper presents a novel approach to reducing undesirable coupling in antenna arrays
using custom-designed resonators and inverse surrogate modeling. To illustrate the …
using custom-designed resonators and inverse surrogate modeling. To illustrate the …
A Deep convolutional neural network for detecting volcanic thermal anomalies from satellite images
The latest generation of high-spatial-resolution satellites produces measurements of high-
temperature volcanic features at global scale, which are valuable to monitor volcanic activity …
temperature volcanic features at global scale, which are valuable to monitor volcanic activity …
An efficient combination of convolutional neural network and LightGBM algorithm for lung cancer histopathology classification
The most dangerous disease in recent decades is lung cancer. The most accurate method of
cancer diagnosis, according to research, is through the use of histopathological images that …
cancer diagnosis, according to research, is through the use of histopathological images that …
Damage localization in rail section using single AE sensor data: an experimental investigation with deep learning approach
Railways serve as a vital link for global trade and transportation in any country, but the rail
sections are susceptible to damage due to factors such as traffic, extreme environment, and …
sections are susceptible to damage due to factors such as traffic, extreme environment, and …
[HTML][HTML] Deep learning based structural damage identification for the strain field of a subway bolster
Strain-based structural health monitoring technology has been widely used in the field of
transportation. The existing strain damage identification methods have defects such as …
transportation. The existing strain damage identification methods have defects such as …