Attention-Based DSC-ConvLSTM for Multiclass Motor Imagery Classification

<table class="table-group" id="tab2"><tr><td><table class="table"><tr><td class="thead-hr" colspan="6"><hr/></td></tr><tr class="thead"><td class="align_left"> </td><td class="align_center">DeepConvNet</td><td class="align_center">ShallowConvNet</td><td class="align_center">EEGNet-4,2</td><td class="align_center">EEGNet-8,2</td><td class="align_center">Ours</td></tr><tr><td class="thead-hr" colspan="6"><hr/></td></tr><tr><td class="align_left">Number of parameters</td><td class="align_center">152219</td><td class="align_center">40644</td><td class="align_center">796</td><td class="align_center">1716</td><td class="align_center">17972</td></tr><tr class="table-tr"><td colspan="6"><hr class="tbody-hr"/></td></tr></table></td></tr></table>

<div>Number of trainable parameters per model.</div>

Computational Intelligence and Neuroscience

tab2

Table 2

Table 2: Attention-Based DSC-ConvLSTM for Multiclass Motor Imagery Classification 