2 citations · 2 across the 3 of their papers we have counts for
6 papers
CoRe-Net: Co-Operational Regressor Network with Progressive Transfer Learning for Blind Radar Signal Restoration
Muhammad Uzair Zahid, Serkan Kiranyaz, Alper Yildirim +1
Real-world radar signals are frequently corrupted by various artifacts, including sensor noise, echoes, interference, and intentional jamming, differing in type, severity, and dura…
BRSR-OpGAN: Blind Radar Signal Restoration using Operational Generative Adversarial Network
Muhammad Uzair Zahid, Serkan Kiranyaz, Alper Yildirim +1
Objective: Many studies on radar signal restoration in the literature focus on isolated restoration problems, such as denoising over a certain type of noise, while ignoring other t…
Refining Myocardial Infarction Detection: A Novel Multi-Modal Composite Kernel Strategy in One-Class Classification
Muhammad Uzair Zahid, Aysen Degerli, Fahad Sohrab +4
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…
Global ECG Classification by Self-Operational Neural Networks with Feature Injection
Muhammad Uzair Zahid, Serkan Kiranyaz, Moncef Gabbouj
Objective: Global (inter-patient) ECG classification for arrhythmia detection over Electrocardiogram (ECG) signal is a challenging task for both humans and machines. The main reaso…
Robust Peak Detection for Holter ECGs by Self-Organized Operational Neural Networks
Moncef Gabbouj, Serkan Kiranyaz, Junaid Malik +5
Although numerous R-peak detectors have been proposed in the literature, their robustness and performance levels may significantly deteriorate in low-quality and noisy signals acqu…
Robust R-Peak Detection in Low-Quality Holter ECGs using 1D Convolutional Neural Network
Muhammad Uzair Zahid, Serkan Kiranyaz, Turker Ince +5
Noise and low quality of ECG signals acquired from Holter or wearable devices deteriorate the accuracy and robustness of R-peak detection algorithms. This paper presents a generic…