Cargando…
A Hybrid Hand-Crafted and Deep Neural Spatio-Temporal EEG Features Clustering Framework for Precise Emotional Status Recognition
Human emotions are variant with time, non-stationary, complex in nature, and are invoked as a result of human reactions during our daily lives. Continuously detecting human emotions from one-dimensional EEG signals is an arduous task. This paper proposes an advanced signal processing mechanism for e...
Autores principales: | Haq, Qazi Mazhar ul, Yao, Leehter, Rahmaniar, Wahyu, Fawad, Islam, Faizul |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9319601/ https://www.ncbi.nlm.nih.gov/pubmed/35890838 http://dx.doi.org/10.3390/s22145158 |
Ejemplares similares
-
An AI-Inspired Spatio-Temporal Neural Network for EEG-Based Emotional Status
por: Alotaibi, Fahad Mazaed, et al.
Publicado: (2023) -
Emotion Recognition from Spatio-Temporal Representation of EEG Signals via 3D-CNN with Ensemble Learning Techniques
por: Yuvaraj, Rajamanickam, et al.
Publicado: (2023) -
Context-Aware Emotion Recognition in the Wild Using Spatio-Temporal and Temporal-Pyramid Models
por: Do, Nhu-Tai, et al.
Publicado: (2021) -
In praise of hands : contemporary crafts of the world /
Publicado: (1974) -
Automated Cobb Angle Measurement for Adolescent Idiopathic Scoliosis Using Convolutional Neural Network
por: Caesarendra, Wahyu, et al.
Publicado: (2022)