| Título | Towards Emotion Recognition: A Persistent Entropy Application |
|---|---|
| Autores | Gonzalez-Diaz, Rocio , PALUZO HIDALGO, EDUARDO, Quesada, Jose F. |
| Publicación externa | Si |
| Medio | Lect. Notes Comput. Sci. |
| Alcance | Proceedings Paper |
| Naturaleza | Científica |
| Cuartil JCR | 4 |
| Cuartil SJR | 2 |
| Impacto SJR | 0.427 |
| Fecha de publicacion | 01/01/2019 |
| ISI | 000684199500008 |
| DOI | 10.1007/978-3-030-10828-1_8 |
| Abstract | Emotion recognition and classification is a very active area of research. In this paper, we present a first approach to emotion classification using persistent entropy and support vector machines. A topology-based model is applied to obtain a single real number from each raw signal. These data are used as input of a support vector machine to classify signals into 8 different emotions (neutral, calm, happy, sad, angry, fearful, disgust and surprised). |
| Palabras clave | Persistent homology; Persistent entropy; Emotion recognition; Support vector machine |
| Miembros de la Universidad Loyola |
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