1 code implementation • 9 Jun 2023 • Zhengqing Miao, Meirong Zhao
The concept of weight freezing revolves around the idea of reducing certain neurons' influence on the decision-making process for a specific EEG task by freezing specific weights in the fully connected layer during the backpropagation process.
2 code implementations • 4 Apr 2023 • Zhengqing Miao, Meirong Zhao
TSFF-Net comprises four main components: time-frequency representation, time-frequency feature extraction, time-space feature extraction, and feature fusion and classification.
2 code implementations • 29 Mar 2023 • Zhengqing Miao, Xin Zhang, Meirong Zhao, Dong Ming
By incorporating two novel attention modules designed specifically for EEG signals, the channel attention module and the depth attention module, LMDA-Net can effectively integrate features from multiple dimensions, resulting in improved classification performance across various BCI tasks.
3 code implementations • 19 Feb 2022 • Zhengqing Miao, Xin Zhang, Carlo Menon, Yelong Zheng, Meirong Zhao, Dong Ming
Compared to the vanilla EEGNet and ConvNet, the proposed SDDA framework was able to boost the MI classification accuracy by 15. 2%, 10. 2% respectively in IIA dataset, and 5. 5%, 4. 2% in IIB dataset.