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Detection of atrial fibrillation in ECG hand-held devices using a random forest classifier
(
IEEE Computer Society
, 2017 , Conference Paper)
Atrial Fibrillation (AF) is characterized by chaotic electrical impulses in the atria, which leads to irregular heartbeats and can develop blood clots and stroke. Therefore, early detection of AF is crucial for increasing ...
Exploring the effect of image enhancement techniques on COVID-19 detection using chest X-ray images
(
Elsevier
, 2021 , Article)
Computer-aided diagnosis for the reliable and fast detection of coronavirus disease (COVID-19) has become a necessity to prevent the spread of the virus during the pandemic to ease the burden on the healthcare system. Chest ...
Personalized Monitoring and Advance Warning System for Cardiac Arrhythmias
(
Nature Publishing Group
, 2017 , Article)
Each year more than 7 million people die from cardiac arrhythmias. Yet no robust solution exists today to detect such heart anomalies right at the moment they occur. The purpose of this study was to design a personalized ...
Dual and single polarized sar image classification using compact convolutional neural networks
(
MDPI AG
, 2019 , Article)
Accurate land use/land cover classification of synthetic aperture radar (SAR) images plays an important role in environmental, economic, and nature related research areas and applications. When fully polarimetric SAR data ...
Blind ECG Restoration by Operational Cycle-GANs
(
IEEE Computer Society
, 2022 , Article)
Objective: ECG recordings often suffer from a set of artifacts with varying types, severities, and durations, and this makes an accurate diagnosis by machines or medical doctors difficult and unreliable. Numerous studies ...
ML-Based Handover Prediction and AP Selection in Cognitive Wi-Fi Networks
(
Springer
, 2022 , Article)
Device mobility in dense Wi-Fi networks offers several challenges. Two well-known problems related to device mobility are handover prediction and access point selection. Due to the complex nature of the radio environment, ...
Data enrichment in fine-grained classification of aquatic macroinvertebrates
(
Institute of Electrical and Electronics Engineers Inc.
, 2017 , Conference Paper)
The types and numbers of benthic macroinverte-brates found in a water body reflect water quality. Therefore, macroinvertebrates are routinely monitored as a part of freshwater ecological quality assessment. The collected ...
Training Radial Basis Function Neural Networks for Classification via Class-Specific Clustering
(
Institute of Electrical and Electronics Engineers Inc.
, 2016 , Article)
In training radial basis function neural networks (RBFNNs), the locations of Gaussian neurons are commonly determined by clustering. Training inputs can be clustered on a fully unsupervised manner (input clustering), or ...
Real-time vibration-based structural damage detection using one-dimensional convolutional neural networks
(
Academic Press
, 2017 , Article)
Structural health monitoring (SHM) and vibration-based structural damage detection have been a continuous interest for civil, mechanical and aerospace engineers over the decades. Early and meticulous damage detection has ...
Real-Time Motor Fault Detection by 1-D Convolutional Neural Networks
(
Institute of Electrical and Electronics Engineers Inc.
, 2016 , Article)
Early detection of the motor faults is essential and artificial neural networks are widely used for this purpose. The typical systems usually encapsulate two distinct blocks: feature extraction and classification. Such ...