<p>Representation of the average features of each layer in CNN-2 using ambulatory SSVEP data. In layer <i>F</i><sub>3</sub>, blue is 9 Hz; red, 11 Hz; green, 13 Hz; black, 15 Hz; and cyan, 17 Hz.</p
(A) Spearman rank correlation coefficients between IT and peak CNN layer similarities are shown for ...
The input is 8x192 EMG data. In each phase, the features are obtained by applying convolution, batch...
Eight visual fields correctly discriminated by the CNN: control cases from the BD data set with G pr...
<p>Learning curve of subjects S2 (black) and S4 (red) using static (solid) and ambulatory (dash line...
<p>Decoding trends of CNN1 compared with CCA-KNN by the number of training data in static SSVEP (a) ...
<p>Each waveform represents the average of all 256 electrodes. Lowest layers are in darker colors, a...
Red parts indicate the areas of the frequency rate projections that are used by classifier to predic...
Performance comparison of CNN models with different region sizes and other baseline models.</p
(A, B). Gray curves show the Pearson correlation coefficients between the mean neural distances and ...
Visualisation of the feature importance for the HC-CNN with two clusters found using FCM, cluster 1 ...
Supplemental Figure 2. A visual representation of the total power of each of the individual frequenc...
<p>Black line indicates mean with shaded gray region reflecting 95% confidence interval. Top line in...
<p>Upper panel: The features selected in the VaD patients. The node size is proportional to the freq...
Receiver Operating Characteristic curve for our CNN model and the transfer-learned Inception v3 mode...
A. Visual representation of the CNN model using Net2Vis [44], B. training and validation loss curves...
(A) Spearman rank correlation coefficients between IT and peak CNN layer similarities are shown for ...
The input is 8x192 EMG data. In each phase, the features are obtained by applying convolution, batch...
Eight visual fields correctly discriminated by the CNN: control cases from the BD data set with G pr...
<p>Learning curve of subjects S2 (black) and S4 (red) using static (solid) and ambulatory (dash line...
<p>Decoding trends of CNN1 compared with CCA-KNN by the number of training data in static SSVEP (a) ...
<p>Each waveform represents the average of all 256 electrodes. Lowest layers are in darker colors, a...
Red parts indicate the areas of the frequency rate projections that are used by classifier to predic...
Performance comparison of CNN models with different region sizes and other baseline models.</p
(A, B). Gray curves show the Pearson correlation coefficients between the mean neural distances and ...
Visualisation of the feature importance for the HC-CNN with two clusters found using FCM, cluster 1 ...
Supplemental Figure 2. A visual representation of the total power of each of the individual frequenc...
<p>Black line indicates mean with shaded gray region reflecting 95% confidence interval. Top line in...
<p>Upper panel: The features selected in the VaD patients. The node size is proportional to the freq...
Receiver Operating Characteristic curve for our CNN model and the transfer-learned Inception v3 mode...
A. Visual representation of the CNN model using Net2Vis [44], B. training and validation loss curves...
(A) Spearman rank correlation coefficients between IT and peak CNN layer similarities are shown for ...
The input is 8x192 EMG data. In each phase, the features are obtained by applying convolution, batch...
Eight visual fields correctly discriminated by the CNN: control cases from the BD data set with G pr...
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