Name
Title | ||
|---|---|---|
Making Sense of Spatio-Temporal Preserving Representations for EEG-Based Human Intention Recognition. |
Abstract | ||
|---|---|---|
Brain-computer interface (BCI) is a system empowering humans to communicate with or control the outside world with exclusively brain intentions. Electroencephalography (EEG)-based BCI is one of the promising solutions due to its convenient and portable instruments. Despite the extensive research of EEG in recent years, it is still challenging to interpret EEG signals effectively due to its nature ... |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1109/TCYB.2019.2905157 | IEEE Transactions on Cybernetics |
Keywords | DocType | Volume |
Electroencephalography,Electrodes,Brain modeling,Feature extraction,Biological neural networks,Recurrent neural networks | Journal | 50 |
Issue | ISSN | Citations |
7 | 2168-2267 | 15 |
PageRank | References | Authors |
0.61 | 27 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Dalin Zhang | 1 | 44 | 6.16 |
| Lina Yao | 2 | 981 | 93.63 |
| Kaixuan Chen | 3 | 47 | 4.80 |
| Sen Wang | 4 | 477 | 37.24 |
| Xiaojun Chang | 5 | 1585 | 76.85 |
| Yunhao Liu | 6 | 8810 | 486.66 |