<p>The classification performance is compared between the four-layer network features in Method I and the single layer network features in Method II on 20 training/test groups. Each group contains 150 training samples and 75 test samples randomly partitioned from our data set.</p
<p>Performance comparisons of multiple individual classifiers on the training dataset by 10-fold cro...
<p>Comparison of the learning accuracies using all the multi-scale features or only global graph fea...
<p>The data from the initial RSVP sequences in the testing phase are used. The median (the central m...
<p>The classification performance is compared between our proposed method (four-layer network featur...
<p>Classification comparison using network features and volumetric features with different numbers o...
<p>The classification accuracy is plotted over different number of training samples. For a given num...
Comparison of the classification performance by the proposed network and other methods.</p
Comparison of the average classification accuracy of the networks used in DeephESC and DeephESC 2.0....
<p>a) Comparison of the accuracy obtained by the proposed method (left side) and the classical netwo...
<p>Comparison of prediction performance of classifiers in terms of F2 score, at different levels hie...
a<p>The number of clusters in the network is determined automatically by the algorithms.</p>b<p>The ...
<p>Comparison of prediction performance of classifiers in terms of AUC score, at different levels hi...
<p>Comparison of prediction accuracy on four multiclass classification datasets by varying the numbe...
<p>The classification accuracy is plotted over different number of training samples. For a given num...
<p>A comparison of the training performance, test accuracy, and uncertainty among classifiers in var...
<p>Performance comparisons of multiple individual classifiers on the training dataset by 10-fold cro...
<p>Comparison of the learning accuracies using all the multi-scale features or only global graph fea...
<p>The data from the initial RSVP sequences in the testing phase are used. The median (the central m...
<p>The classification performance is compared between our proposed method (four-layer network featur...
<p>Classification comparison using network features and volumetric features with different numbers o...
<p>The classification accuracy is plotted over different number of training samples. For a given num...
Comparison of the classification performance by the proposed network and other methods.</p
Comparison of the average classification accuracy of the networks used in DeephESC and DeephESC 2.0....
<p>a) Comparison of the accuracy obtained by the proposed method (left side) and the classical netwo...
<p>Comparison of prediction performance of classifiers in terms of F2 score, at different levels hie...
a<p>The number of clusters in the network is determined automatically by the algorithms.</p>b<p>The ...
<p>Comparison of prediction performance of classifiers in terms of AUC score, at different levels hi...
<p>Comparison of prediction accuracy on four multiclass classification datasets by varying the numbe...
<p>The classification accuracy is plotted over different number of training samples. For a given num...
<p>A comparison of the training performance, test accuracy, and uncertainty among classifiers in var...
<p>Performance comparisons of multiple individual classifiers on the training dataset by 10-fold cro...
<p>Comparison of the learning accuracies using all the multi-scale features or only global graph fea...
<p>The data from the initial RSVP sequences in the testing phase are used. The median (the central m...
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