Electrical Engineering: Recent submissions
Now showing items 21-40 of 2886
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Transfer Learning Across Heterogeneous Structures Through Adversarial Training
( Springer , 2025 , Conference)Transfer learning (TL) methods have become increasingly crucial for the challenges in gathering accurately labeled data from various structures in structural health monitoring (SHM) tasks, such as structural damage detection ... -
Surveillance, prevention, and control of infectious diseases: An AI perspective
( Springer , 2024 , Book)This is a pioneering book that delves into the intersection of artificial intelligence (AI) and healthcare, specifically focusing on the detection and prevention of infectious diseases. Authored by leading experts in the ... -
Super Neurons
( IEEE , 2024 , Article)Self-Organized Operational Neural Networks (Self-ONNs) have recently been proposed as new-generation neural network models with nonlinear learning units, i.e., the generative neurons that yield an elegant level of diversity; ... -
Operational Neural Networks for Parameter-Efficient Hyperspectral Single-Image Super-Resolution
( IEEE , 2024 , Article)Hyperspectral imaging is a crucial tool in remote sensing, which captures far more spectral information than standard color images. However, the increase in spectral information comes at the cost of spatial resolution. ... -
Exploring Sound Versus Vibration for Robust Fault Detection on Rotating Machinery
( IEEE , 2024 , Article)Robust and real-time detection of faults has become an ultimate objective for predictive maintenance on rotating machinery. Vibration-based deep learning (DL) methodologies have become the de facto standard for bearing ... -
REFINING MYOCARDIAL INFARCTION DETECTION: A NOVEL MULTI-MODAL COMPOSITE KERNEL STRATEGY IN ONE-CLASS CLASSIFICATION
( IEEE , 2024 , Conference)Early detection of myocardial infarction (MI), a critical condition arising from coronary artery disease (CAD), is vital to prevent further myocardial damage. This study introduces a novel method for early MI detection ... -
Real-Time Vibration-Based Bearing Fault Diagnosis Under Time-Varying Speed Conditions
( IEEE , 2024 , Conference)Detection of rolling-element bearing faults is crucial for implementing proactive maintenance strategies and for minimizing the economic and operational consequences of unexpected failures. However, many existing techniques ... -
SAF-Net: Self-Attention Fusion Network for Myocardial Infarction Detection Using Multi-View Echocardiography
( IEEE , 2023 , Conference)Myocardial infarction (MI) is a severe case of coronary artery disease (CAD) and ultimately, its detection is sub-stantial to prevent progressive damage to the myocardium. In this study, we propose a novel view-fusion model ... -
Zero-shot motor health monitoring by blind domain transition
( Elsevier , 2024 , Article)Continuous long-term monitoring of motor health is crucial for the early detection of abnormalities such as bearing faults (up to 51% of motor failures are attributed to bearing faults). Despite numerous methodologies ... -
R2C-GAN: Restore-to-Classify Generative Adversarial Networks for blind X-ray restoration and COVID-19 classification
( Elsevier , 2024 , Article)Restoration of poor-quality medical images with a blended set of artifacts plays a vital role in a reliable diagnosis. As a pioneer study in blind X-ray restoration, we propose a joint model for generic image restoration ... -
Restoration of magnetohydrodynamic-corrupted 12-lead electrocardiogram to enhance cardiac monitoring during magnetic resonance imaging
( Elsevier , 2024 , Article)The Magnetohydrodynamic (MHD) effect on the bloodstream, induced by the static magnetic field of Magnetic Resonance Imaging (MRI) devices, distorts Electrocardiogram (ECG) components, and poses challenges to cardiac gating ... -
Deep learning in automated power line inspection: A review
( Elsevier , 2025 , Article)In recent years, power line maintenance has seen a paradigm shift by moving towards computer vision-powered automated inspection. The utilization of an extensive collection of videos and images has become essential for ... -
Multi-Source Transfer Learning for zero-shot Structural Damage Detection
( Elsevier , 2025 , Article)Developing generalizable Structural Health Monitoring (SHM) tools for downstream tasks, such as Structural Damage Detection (SDD), is one way to tackle large-scale SHM applications. Such tools become particularly important ... -
Wearable wrist to finger photoplethysmogram translation through restoration using super operational neural networks based 1D-CycleGAN for enhancing cardiovascular monitoring
( Elsevier , 2024 , Article)Background and MotivationsPhysiological signals, such as the Photoplethysmogram (PPG) collected through wearable devices, consistently encounter significant motion artifacts. Current signal processing techniques, and even ... -
Early myocardial infarction detection over multi-view echocardiography
( Elsevier , 2024 , Article)Myocardial infarction (MI) is the leading cause of mortality in the world. Its early diagnosis can mitigate the extent of myocardial damage by facilitating early therapeutic interventions. The regional wall motion abnormality ... -
Enhanced coronary artery segmentation and stenosis detection: Leveraging novel deep learning techniques
( Elsevier , 2025 , Article)Coronary artery disease (CAD) is a significant global health concern, emphasizing the need for reliable and automated diagnostic solutions. This study proposes a novel deep learning framework aimed at improving both full ... -
Violations and Work Characteristics of Motorcycle Food Delivery Riders: A Case Study in Qatar
( Elsevier , 2025 , Conference)Motorcycle food delivery riders (MFDRs) in Qatar often face significant time pressure to avoid penalties and maximize their earnings by completing more trips per day. This study examines the relationship between self-reported ... -
Multi-class subarachnoid hemorrhage severity prediction: addressing challenges in predicting rare outcomes
( Springer Nature Link , 2025 , Article)Accurately predicting the severity of subarachnoid hemorrhage (SAH) is critical for informing clinical decisions and improving patient outcomes. This study addresses the challenges of imbalanced data in SAH severity ... -
Neural signals, machine learning, and the future of inner speech recognition
( Frontiers , 2025 , Article)Inner speech recognition (ISR) is an emerging field with significant potential for applications in brain-computer interfaces (BCIs) and assistive technologies. This review focuses on the critical role of machine learning ... -
Performance Evaluation of Artificial Intelligence Techniques in the Diagnosis of Brain Tumors: A Systematic Review and Meta-Analysis.
( Springer Nature , 2025 , Article Review)Brain tumors are becoming more prevalent, often leading to severe disability and high mortality rates due to their poor prognoses. Early detection is critical for improving patient outcomes. These tumors pose substantial ...
