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braindecode

Outdated, see new https://github.com/braindecode/braindecode

eeg-based-emotion-analysis-using-deap-dataset-for-supervised-machine-learning

This project is for classification of emotions using EEG signals recorded in the DEAP dataset to achieve high accuracy score using machine learning algorithms such as Support vector machine and K - Nearest Neighbor.

eeg-datasets

A list of all public EEG-datasets

eeg-emotion-classification

eeg_emotion_feature_engineering

emotion-detection

emotion-detection-from-eeg

KNN classifier for human emotion from EEG

emotion-recognition

EEG-based emotion recognition framework including an eye tracking sequence classifier and a WGAN model

emotion-recognition-1

Emotion recognition from EEG and physiological signals using deep neural networks

emotionclassifier

Emotion classifer based on EEG singnals

firstgit

jda

Domain Adaptation for EEG Emotion Recognition Based on Latent Representation Similarity

mlseed

Emotion Recognition using ML methods on the SEED dataset

multi-souce-separation-and-alignment-network-for-eeg-emotion-classification

Transfer learning for multi source EEG-emotion-classification

semimvae

Semi-supervised Multi-view Variational Autoencoder (semiMVAE)

style-transfer-mapping

Multisource Transfer Learning for Cross- Subject EEG Emotion Recognition

tsception

PyTorch implementation of TSception

wassersteingan