Cargando…
Local domain generalization with low-rank constraint for EEG-based emotion recognition
As an important branch in the field of affective computing, emotion recognition based on electroencephalography (EEG) faces a long-standing challenge due to individual diversities. To conquer this challenge, domain adaptation (DA) or domain generalization (i.e., DA without target domain in the train...
Autores principales: | Tao, Jianwen, Dan, Yufang, Zhou, Di |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10662311/ https://www.ncbi.nlm.nih.gov/pubmed/38027525 http://dx.doi.org/10.3389/fnins.2023.1213099 |
Ejemplares similares
-
Multi-Model Adaptation Learning With Possibilistic Clustering Assumption for EEG-Based Emotion Recognition
por: Dan, Yufang, et al.
Publicado: (2022) -
Possibilistic Clustering-Promoting Semi-Supervised Learning for EEG-Based Emotion Recognition
por: Dan, Yufang, et al.
Publicado: (2021) -
Multi-Source Co-adaptation for EEG-Based Emotion Recognition by Mining Correlation Information
por: Tao, Jianwen, et al.
Publicado: (2021) -
Robust Latent Multi-Source Adaptation for Encephalogram-Based Emotion Recognition
por: Tao, Jianwen, et al.
Publicado: (2022) -
Possibilistic distribution distance metric: a robust domain adaptation learning method
por: Tao, Jianwen, et al.
Publicado: (2023)