Fig. 12From: Exploring spatial-frequency-sequential relationships for motor imagery classification with recurrent neural networkThe classification accuracy performances for all subjects with all algorithms. CNN and SVM (Linear) outperforms RNN in some subjects with high-level (over 60%) accuracies (S3, S7, S8, S9 in “Dataset 2a” and S4, S6, S8, S9 in “Dataset 2b”). However, in low-level (below 60%) accuracies of subjects, RNN outperforms CNN and SVM-Linear (S2, S4, S6 in “Dataset 2a” and S2, S3 in for “Dataset 2b”). In the average-level accuracies, RNN outperforms CNN and SVM (Linear). a Classification accuracy performances for “Dataset 2a” and b Classification accuracy performances for “Dataset 2b”Back to article page