most citedCardioPatternFormer: Pattern-Guided Attention for Interpretable ECG Classification with Transformer Architecture

1 citations · 1 across the 5 of their papers we have counts for

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5 papers

cs.CV2025

Super-Resolution Generative Adversarial Networks based Video Enhancement

Kağan Çetin, Hacer Akça, Ömer Nezih Gerek

This study introduces an enhanced approach to video super-resolution by extending ordinary Single-Image Super-Resolution (SISR) Super-Resolution Generative Adversarial Network (SRG…

eess.AS2025

Hybrid Deep Learning and Signal Processing for Arabic Dialect Recognition in Low-Resource Settings

Ghazal Al-Shwayyat, Omer Nezih Gerek

Arabic dialect recognition presents a significant challenge in speech technology due to the linguistic diversity of Arabic and the scarcity of large annotated datasets, particularl…

eess.SP20251 cited

CardioPatternFormer: Pattern-Guided Attention for Interpretable ECG Classification with Transformer Architecture

Berat Kutay Uğraş, Ömer Nezih Gerek, İbrahim Talha Saygı

Accurate ECG interpretation is vital, yet complex cardiac data and "black-box" AI models limit clinical utility. Inspired by Transformer architectures' success in NLP for understan…

eess.IV2023

Low-Dose CT Image Enhancement Using Deep Learning

A. Demir, M. M. A. Shames, O. N. Gerek +6

The application of ionizing radiation for diagnostic imaging is common around the globe. However, the process of imaging, itself, remains to be a relatively hazardous operation. Th…

cs.LG2023

Are Deep Learning Classification Results Obtained on CT Scans Fair and Interpretable?

Mohamad M. A. Ashames, Ahmet Demir, Omer N. Gerek +6

Following the great success of various deep learning methods in image and object classification, the biomedical image processing society is also overwhelmed with their applications…