Developing a Deep Learning Based Approach for Anomalies Detection from EEG Data
Download
Download
Download
Full text for this resource is not available from the Research Repository.
Export
Alvi, Ashik Mostafa 
ORCID: https://orcid.org/0000-0001-7898-2030, Siuly, Siuly ORCID: https://orcid.org/0000-0003-2491-0546 and Wang, Hua ORCID: https://orcid.org/0000-0002-8465-0996
(2021)
Developing a Deep Learning Based Approach for Anomalies Detection from EEG Data.
In: 22nd International Conference on Web Information Systems Engineering, WISE 2021, 26-29 Oct 2021, Melbourne, Australia.
Dimensions Badge
Altmetric Badge
| Item type | Conference or Workshop Item (Paper) |
| URI | https://vuir.vu.edu.au/id/eprint/43217 |
| DOI | 10.1007/978-3-030-90888-1_45 |
| Official URL | https://link.springer.com/chapter/10.1007/978-3-03... |
| ISBN | 9783030908874 |
| Subjects | Current > FOR (2020) Classification > 4605 Data management and data science Current > FOR (2020) Classification > 4611 Machine learning Current > Division/Research > First Year College Current > Division/Research > Institute for Sustainable Industries and Liveable Cities |
| Keywords | EEG, deep learning, electroencephalography, traditional machine learning, TMC |
| Citations in Scopus | 12 - View on Scopus |
| Download/View statistics | View download statistics for this item |
CORE (COnnecting REpositories)