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 paper we present the differentiable log-Mel spectrogram (DMEL) for audio classification. DMEL uses a Gaussian window, with a window length that can be jointly optimized with the ...
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 ...