Open Access
| Issue |
ITM Web Conf.
Volume 47, 2022
2022 2nd International Conference on Computer, Communication, Control, Automation and Robotics (CCCAR2022)
|
|
|---|---|---|
| Article Number | 02041 | |
| Number of page(s) | 6 | |
| Section | Algorithm Optimization and Application | |
| DOI | https://doi.org/10.1051/itmconf/20224702041 | |
| Published online | 23 June 2022 | |
- Esposito R, Bortoletto M, Miniussi C. Integrating TMS, EEG, and MRI as an approach for studying brain connectivity [J]. Neuroscientist, 2020, 26(5-6): 471-486. [CrossRef] [Google Scholar]
- Liao L H C. Research and application of emotion recognition method based on physiological signal [D]. University of Electronic Science and Technology of China, 2020. [Google Scholar]
- Yang Y L, Wu Q, Fu Y, et al. Continuous convolutional neural network with 3d input for EEG-based emotion recognition[C]. Proceedings of the International Conference on Neural Information Processing. Berlin: Springer, 2018: 433-443. [Google Scholar]
- Kwon Y H, Shin S B, Kim S D. Electroencephalography based fusion two-dimensional (2D)-convolutional neural network model for emotion recognition system [J]. Sensors, 2018, 18(5): 1383. [CrossRef] [Google Scholar]
- Yang X L, Lin S Z. Method for multi-band image feature-level fusion based on the attention mechanism [J]. Journal of Xidian University, 2020, 47(01):120-127. [Google Scholar]
- Wang Y, Huang ZY, McCane B, Neo P. EmotioNet: a 3-D convolutional neural network for EEG-based emotion recognition. In: 2018 international joint conference on neural networks. [Google Scholar]
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.