The deep learning methods employed include MLP (Multilayer Perceptron), CNN (Convolutional Neural Network), and RNN (Recurrent Neural Network). The experimental results indicate that deep learning ...

The resurgence of artificial intelligence enabled by deep learning and high performance computing has seen a dramatic increase of demand in the accuracy of deep learning model which has come at the ...

Training and evaluation pipeline for MEG and EEG brain signal encoding and decoding using deep learning. Code for our paper "Decoding speech perception from non-invasive brain recordings" published in ...

This study presents a useful method for the extraction of behaviour-related activity from neural population recordings based on a specific deep learning architecture, a variational autoencoder.

Deep learning-based encryption, which leverages the nonlinear characteristics of neural networks, has emerged as a promising new method for protecting medical images. In this paper, we present ...

This study presents a deep-learning-assisted microfluidic immunoassay platform that uses a smartphone-based imaging transcoding system, ... The “encoding–decoding” strategy and integrated microfluidic ...

(2025, February 17). A geometric deep learning method for decoding brain dynamics. ScienceDaily. Retrieved June 11, 2025 from www.sciencedaily.com / releases / 2025 / 02 / 250217133453.htm.

A recent development in deep learning techniques has attracted attention to the decoding and classification of electroencephalogram (EEG) signals. ... Citation: Singh AK and Bianchi L (2024) Encoding ...