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).

Abstract: The reassignment technique is used to increase localization for signal components in the time-frequency representation. The technique gives perfect localization for linear chirp signals and ...

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 ...

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 ...

Abstract: In this study, we explore the use of Vector Quantized Variational Autoencoders (VQ-VAE) for real-time audio spectrogram inpainting, with a focus on minimizing environmental impact. We ...