ECG Classification with Dual Models: XGBoost Voting and Deep Learning with Attention

Y Li, Y Hu, J Chen, B Wang… - 2023 16th International …, 2023 - ieeexplore.ieee.org
During the process of Electrocardiogram (ECG) recognition, frequent challenges arise
concerning the lack of convenience and accuracy. Moreover, the imbalanced distribution of …

Research on the application of deep learning based surface defect detection and treatment method for hot rolled strip steel

X Feng, X Gao, L Luo - 2022 41st Chinese Control Conference …, 2022 - ieeexplore.ieee.org
Current research on the detection of surface defects in hot-rolled strip steel is mainly focused
on defects in the hot-rolling stage, and there is less research on surface defects in hot-rolled …

Application of deep learning in civil engineering management

H Zhao - Computational intelligence and neuroscience, 2022 - Wiley Online Library
Construction safety issues are of great significance in civil engineering management. In this
paper, the entry point is the recognition of workers wearing helmets during the construction …

[PDF][PDF] Collateral Circulation Classification Based on Cone Beam Computed Tomography Images using ResNet18 Convolutional Neural Network

NH Ali, AR Abdullah, N Mohd Saad… - International Journal of …, 2023 - researchgate.net
Collateral circulation is an arterial anastomotic channel that supply nutrient perfusion to
areas of the brain. It happens when there is an existence of disruption of regular sources of …

Multimodal Arrhythmia Classification Using Deep Neural Networks

I Cretu, A Tindale, M Abbod, A Khir, W Balachandran… - 2023 - bura.brunel.ac.uk
Arrhythmias are deviations from the normal heart rhythm with impact on the cardiovascular
health. Their prompt detection plays an important role in mitigating potential negative …

Deep learning for ECG signal classification in remote healthcare applications

SA Hashim, HH Balik - International Conference on Advanced Engineering …, 2023 - Springer
Due to several current medical applications, the significance of Electrocardiogram (ECG)
classification has increased significantly. To evaluate and classify ECG data, a variety of …

Automated Heartbeat Classification for Arrhythmia Patients Using a Deep Convolutional Neural Network

S Kerdoudi, L Guezouli, A Hattab… - 2024 8th International …, 2024 - ieeexplore.ieee.org
The electrocardiogram (ECG) is widely used for diagnosing heart diseases, including
arrhythmia, due to its noninvasive nature and simplicity. Accurate detection and …

A SAR Target Recognition Method via Combination of Multilevel Deep Features

J Wang, Y Jiang - Computational Intelligence and …, 2021 - Wiley Online Library
For the problem of synthetic aperture radar (SAR) image target recognition, a method via
combination of multilevel deep features is proposed. The residual network (ResNet) is used …

Internet of things horizontal platform development for expanded application scenarios and use cases

I Ganchev, Z Ji, M O'Droma - Journal of Physics: Conference …, 2023 - iopscience.iop.org
This paper presents the horizontal approach for the development of Internet of Things (IoT)
platforms, based on a generic, multi-service, cloud-based IoT operational platform, called …

A method to detect sleep apnea using residual attention mechanism network from single-lead ECG signal

T Wang, C Lu, Y Sun, H Fang, W Jiang… - Biomedical Engineering …, 2022 - degruyter.com
Sleep apnea is a sleep disorder caused by weakened or suspended breathing during sleep,
which seriously affects the work and health of patients. The traditional polysomnography …