[HTML][HTML] Automated damage diagnosis of concrete jack arch beam using optimized deep stacked autoencoders and multi-sensor fusion
A novel hybrid framework of optimized deep learning models combined with multi-sensor
fusion is developed for condition diagnosis of concrete arch beam. The vibration responses …
fusion is developed for condition diagnosis of concrete arch beam. The vibration responses …
Classifying cardiac arrhythmia from ECG signal using 1D CNN deep learning model
Blood circulation depends critically on electrical activation, where any disturbance in the
orderly pattern of the heart's propagating wave of excitation can lead to arrhythmias …
orderly pattern of the heart's propagating wave of excitation can lead to arrhythmias …
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 …
Deep learning of electromechanical impedance for concrete structural damage identification using 1-D convolutional neural networks
D Ai, F Mo, J Cheng, L Du - Construction and Building Materials, 2023 - Elsevier
Common damages in concrete materials and structures are usually in small sizes at initial
stage, which induce small stiffness and mass loss being difficult to evaluate severity level …
stage, which induce small stiffness and mass loss being difficult to evaluate severity level …
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 …
Computer-aided detection and classification of monkeypox and chickenpox lesion in human subjects using deep learning framework
Monkeypox is a zoonotic viral disease caused by the monkeypox virus. After its recent
outbreak, it has become clear that a rapid, accurate, and reliable diagnosis may help reduce …
outbreak, it has become clear that a rapid, accurate, and reliable diagnosis may help reduce …
Prediction of mechanical properties of high‐performance concrete and ultrahigh‐performance concrete using soft computing techniques: A critical review
A cement‐based material that meets the general goals of mechanical properties, workability,
and durability as well as the ever‐increasing demands of environmental sustainability is …
and durability as well as the ever‐increasing demands of environmental sustainability is …
ssFPN: Scale Sequence (S2) Feature-Based Feature Pyramid Network for Object Detection
Object detection is a fundamental task in computer vision. Over the past several years,
convolutional neural network (CNN)-based object detection models have significantly …
convolutional neural network (CNN)-based object detection models have significantly …
Design of efficient methods for the detection of tomato leaf disease utilizing proposed ensemble CNN model
H Ulutaş, V Aslantaş - Electronics, 2023 - mdpi.com
Early diagnosis of plant diseases is of vital importance since they cause social, ecological,
and economic losses. Therefore, it is highly complex and causes excessive workload and …
and economic losses. Therefore, it is highly complex and causes excessive workload and …