activity
20242026
collaborators

14 papers

cs.CV2026

EPRA U-Net: An Efficient Pyramid Residual Attention Framework for Accurate Infarct Segmentation in Diffusion-Weighted MRI

Hasan Ulutas, Muhammet Emin Sahin, Mustafa Fatih Erkoc +4

Objective: Accurate identification of acute ischemic infarcts on diffusion-weighted magnetic resonance imaging (DWI) is a critical prerequisite for reliable lesion quantification a…

cs.LG2026

Axiomatizing Neural Networks via Pursuit of Subspaces

Mehmet Yamac, Mert Duman, Ugur Akpinar +4

While deep neural networks have achieved remarkable success across a wide range of domains, their underlying mechanisms remain poorly understood, and they are often regarded as bla…

eess.IV2026

MTS-CSNet: Multiscale Tensor Factorization for Deep Compressive Sensing on RGB Images

Mehmet Yamac, Lei Xu, Serkan Kiranyaz +1

Deep learning based compressive sensing (CS) methods typically learn sampling operators using convolutional or block wise fully connected layers, which limit receptive fields and s…

cs.LG2026

Real-Time Vibration-Based Bearing Fault Diagnosis Under Time-Varying Speed Conditions

Tuomas Jalonen, Mohammad Al-Sa'd, Serkan Kiranyaz +1

Detection of rolling-element bearing faults is crucial for implementing proactive maintenance strategies and for minimizing the economic and operational consequences of unexpected…

cs.LG2026

Dual-Domain Fusion for Semi-Supervised Learning

Tuomas Jalonen, Mohammad Al-Sa'd, Serkan Kiranyaz +1

Labeled time-series data is often expensive and difficult to obtain, making it challenging to train accurate machine learning models for real-world applications such as anomaly det…

cs.LG2026

Fusion of Quadratic Time-Frequency Analysis and Convolutional Neural Networks to Diagnose Bearing Faults Under Time-Varying Speeds

Mohammad Al-Sa'd, Tuomas Jalonen, Serkan Kiranyaz +1

Diagnosis of bearing faults is paramount to reducing maintenance costs and operational breakdowns. Bearing faults are primary contributors to machine vibrations, and analyzing thei…