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Joint learning and optimization for Federated Learning in NOMA-based networks
(
Elsevier
, 2023 , Article)
Over the past decade, the usage of machine learning (ML) techniques have increased substantially in different applications. Federated Learning (FL) refers to collaborative techniques that avoid the exchange of raw data ...
Distributed Inference in Resource-Constrained IoT for Real-Time Video Surveillance
(
IEEE
, 2023 , Article)
Advances in communication technologies and computational capabilities of Internet of Things (IoT) devices enable a range of complex applications that require ever increasing processing of sensors' data. An illustrative ...
Convolutional Neural Networks for patient-specific ECG classification
(
IEEE
, 2015 , Conference Paper)
We propose a fast and accurate patient-specific electrocardiogram (ECG) classification and monitoring system using an adaptive implementation of 1D Convolutional Neural Networks (CNNs) that can fuse feature extraction and ...
OSEGNET: OPERATIONAL SEGMENTATION NETWORK FOR COVID-19 DETECTION USING CHEST X-RAY IMAGES
(
IEEE
, 2022 , Conference Paper)
Coronavirus disease 2019 (COVID-19) has been diagnosed automatically using Machine Learning algorithms over chest X-ray (CXR) images. However, most of the earlier studies used Deep Learning models over scarce datasets ...
RELIABLE COVID-19 DETECTION USING CHEST X-RAY IMAGES
(
IEEE Computer Society
, 2021 , Conference Paper)
Coronavirus disease 2019 (COVID-19) has emerged the need for computer-aided diagnosis with automatic, accurate, and fast algorithms. Recent studies have applied Machine Learning algorithms for COVID-19 diagnosis over chest ...
Biosignal time-series analysis
(
Elsevier
, 2022 , Book chapter)
In this chapter, recent state-of-the-art techniques in biosignal time-series analysis will be presented. We shall start with the problem of patient-specific ECG beat classification where the objective is to discriminate ...
SRL-SOA: SELF-REPRESENTATION LEARNING WITH SPARSE 1D-OPERATIONAL AUTOENCODER FOR HYPERSPECTRAL IMAGE BAND SELECTION
(
IEEE Computer Society
, 2022 , Conference Paper)
The band selection in the hyperspectral image (HSI) data processing is an important task considering its effect on the computational complexity and accuracy. In this work, we propose a novel framework for the band selection ...
Early Myocardial Infarction Detection with One-Class Classification over Multi-view Echocardiography
(
IEEE Computer Society
, 2022 , Conference Paper)
Myocardial infarction (MI) is the leading cause of mortaZity and morbidity in the world. Early therapeutics of MI can ensure the prevention of further myocardial necrosis. Echocardiography is the fundamental imaging technique ...
Improved Domain Adaptation Approach for Bearing Fault Diagnosis
(
IEEE Computer Society
, 2022 , Conference Paper)
Application of domain adaptation techniques to predictive maintenance of modern electric rotating machinery (RM) has significant potential with the goal of transferring or adaptation of a fault diagnosis model developed ...
BM3D VS 2-LAYER ONN
(
IEEE Computer Society
, 2021 , Conference Paper)
Despite their recent success on image denoising, the need for deep and complex architectures still hinders the practical usage of CNNs. Older but computationally more efficient methods such as BM3D remain a popular choice, ...