GitHub

Making Acoustic Side-Channel Attacks on Noisy Keyboards Viable with LLM-Assisted Spectrograms "Typo" Correction

This repo is the implementation of a research project aimed at enhancing Acoustic Side-Channel Attacks (ASCAs) using a novel combination of Vision Transformers (VTs) and Large Language Models (LLMs).
IEEE

Model-Guided Deep Learning for Line Segment Detection in Time–Frequency Spectrograms of an Ocean Waveguide

Abstract: The application of machine learning in underwater acoustics is often limited by the lack of high-quality data. One method to avoid this data issue is to use modeled data to train a machine ...
Frontiers

Integration of PCG spectrogram texture and deep features for the diagnosis of heart failure with preserved ejection fraction using heterogeneous stacking ensemble learning

This study proposes a novel heterogeneous stacking ensemble learning model for the fusion of phonocardiogram (PCG) spectrogram texture and deep features to detect heart failure with preserved ejection ...
Microsoft

High-Fidelity Synthetic ECG Generation via Mel-Spectrogram Informed Diffusion Training

The development of machine learning for cardiac care is severely hampered by privacy restrictions on sharing real patient electrocardiogram (ECG) data. Although generative AI offers a promising ...
IEEE

An Attention-Enhanced 3D-CNN Framework for Spectrogram-Based EEG Analysis in Epilepsy Detection

Abstract: Epilepsy is a widespread neurological disorder affecting approximately 50 million individuals globally, with a disproportionately high burden in low- and middle-income countries. It is ...