Automated emotion recognition: Current trends and future perspectives
Article
Article Title | Automated emotion recognition: Current trends and future perspectives |
---|---|
ERA Journal ID | 5039 |
Article Category | Article |
Authors | Maithri, M., Raghavendra, U., Gudigar, Anjan, Samanth, Jyothi, Barua, Prabal Datta, Murugappan, Murugappan, Chakole, Yashas and Acharya, U. Rajendra |
Journal Title | Computer Methods and Programs in Biomedicine |
Journal Citation | 215 |
Article Number | 106646 |
Number of Pages | 30 |
Year | 2022 |
Publisher | Elsevier |
Place of Publication | Ireland |
ISSN | 0169-2607 |
1872-7565 | |
Digital Object Identifier (DOI) | https://doi.org/10.1016/j.cmpb.2022.106646 |
Web Address (URL) | https://www.sciencedirect.com/science/article/pii/S0169260722000311 |
Abstract | Background Objective Method Results Conclusion |
Keywords | Human emotions; Electroencephalogram (EEG); Machine learning; CAD; Facial; Voice |
ANZSRC Field of Research 2020 | 400306. Computational physiology |
Public Notes | Files associated with this item cannot be displayed due to copyright restrictions. |
Byline Affiliations | Ngee Ann Polytechnic, Singapore |
Asia University, Taiwan | |
Singapore University of Social Sciences (SUSS), Singapore | |
Manipal Academy of Higher Education, India | |
University of Southern Queensland | |
University of Technology Sydney | |
Kuwait College of Science and Technology, Kuwait |
https://research.usq.edu.au/item/z0266/automated-emotion-recognition-current-trends-and-future-perspectives
70
total views0
total downloads5
views this month0
downloads this month