eLife

High-Fidelity Neural Speech Reconstruction through an Efficient Acoustic-Linguistic Dual-Pathway Framework

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, ...
GitHub

CONVOLUTIONAL-AUTOENCODER-FOR-IMAGE-DENOISING

This code implements a Denoising Autoencoder using PyTorch to clean noisy images from the MNIST dataset. It uses a convolutional neural network architecture, where the encoder compresses the input ...
IEEE

Enhancing DORT Method Performance in Time-Reversal Microwave Imaging Through Denoising Autoencoder

Abstract: We investigate the impact of noise on time-reversal imaging and propose an approach that significantly enhances the detection of objects in noisy environments. Our method involves the ...
GitHub

This project contains a TensorFlow-based Denoising Autoencoder (DAE) to exact model galaxy from observed galaxy images and perform galaxy model subtraction.

Clone this repository to your local machine or cloud service using the following command: To provide a comprehensive overview of the dataset generation process used in your project, it's important to ...
IEEE

RAECAE: A Multi-Scale Attention Residual Convolutional Autoencoder-Based Method for Denoising Vibration Signals of Wind Turbine Rolling Bearings

The rolling bearings of wind turbines operate in complex environments characterized by high temperatures, strong impacts, vibrations, and varying operating conditions. As a result, the collected ...