# siddhi5386/Emotion-Recognition-from-brain-EEG-signals-

<https://repo.masters-masters.com/repos/siddhi5386/Emotion-Recognition-from-brain-EEG-signals->

[Accueil](https://repo.masters-masters.com/) › [siddhi5386](https://repo.masters-masters.com/owners/siddhi5386) › [Emotion-Recognition-from-brain-EEG-signals-](https://repo.masters-masters.com/repos/siddhi5386/Emotion-Recognition-from-brain-EEG-signals-)

siddhi5386/Emotion-Recognition-from-brain-EEG-signals-, dépôt open source à 138 étoiles sur GitHub. Carte Prototype de RepoMasters. Langage : Jupyter Notebook.

| Champ | Valeur |
| --- | --- |
| Propriétaire | [siddhi5386](https://repo.masters-masters.com/owners/siddhi5386) |
| Étoiles | 138 |
| Forks | 27 |
| Langage | [Jupyter Notebook](https://repo.masters-masters.com/languages/jupyter-notebook) |
| Licence | Aucune |
| Création | 2020 |
| Rang | [Prototype (100 à 249 ★)](https://repo.masters-masters.com/ranks/rush) |
| Voir sur GitHub | [siddhi5386/Emotion-Recognition-from-brain-EEG-signals-](https://github.com/siddhi5386/Emotion-Recognition-from-brain-EEG-signals-) |

## Fiche du dépôt

Emotion recognition can be achieved by obtaining signals from the brain by EEG . This test records the activity of the brain in form of waves. We have used DEAP dataset on which we are classifying the emotion as valance, likeness/dislike, arousal, dominance. We have used LSTM and CNN classifier whi…

Rang des dépôts qui ont 100 à 249 ★ sur GitHub. Probabilité publiée par carte tirée : 70 %. Rareté : Commune.

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