This study presents a valuable advance in reconstructing naturalistic speech from intracranial ECoG data using a dual-pathway model. The evidence supporting the claims of the authors is solid, ...

Abstract: Convolutional neural networks (CNNs) show promise for signal denoising but can introduce harmonic distortions due to their nonlinearity. This paper introduces a comprehensive evaluation ...

This project focuses on enhancing brain CT scans by reducing acquisition noise using a CNN-based autoencoder, followed by tumor detection on the refined images. The workflow ensures that critical ...

Abstract: With the rapid development of diffusion models, adversarial examples generated using these models exhibit high quality and have become an emerging attack strategy that is widely studied.

SVG Autoencoder - Uses a frozen representation encoder with a residual branch to compensate the information loss and a learned convolutional decoder to transfer the SVG latent space to pixel space.