We propose a novel architecture called MI-CAT. The architecture innovatively utilizes Transformer's self-attention and cross-attention mechanisms to interact ...
The architecture innovatively utilizes Transformer's self-attention and cross-attention mechanisms to interact features to resolve differential distribution ...
Jun 7, 2023 · We propose a novel architecture called MI-CAT. The architecture innovatively utilizes Transformer's self-attention and cross-attention mechanisms to interact ...
Aug 1, 2023 · MI-CAT: : A transformer-based domain adaptation network for motor imagery classification. Authors: Dongxue Zhang.
To evaluate our method, we conduct extensive experiments on two real public EEG datasets, Dataset IIb and Dataset IIa, achieving competitive performance with an ...
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Aug 30, 2024 · They introduced a cross-attention Transformer domain adaptive network, named MI-CAT. It achieves an average classification accuracy of 76.81% on ...
MI-CAT: A transformer-based domain adaptation network for motor imagery classification · Deep Representation-Based Domain Adaptation for Nonstationary EEG ...
MI-CAT: A transformer-based domain adaptation network for motor imagery classification. Citing Article. June 2023. Neural Networks. Dongxue Zhang. ·. Huiying Li.
MI-CAT: A transformer-based domain adaptation network for motor imagery classification · Computer Science. Neural Networks · 2023.
MI-CAT: A transformer-based domain adaptation network for motor imagery classification. Neural Netw. 2023, 165, 451–462. [Google Scholar] [CrossRef]; Li, H ...