Differential test accuracy gain of different algorithms and proposed ShapAAL from the current reported (best) benchmark results.</p
Performance statistics of the tested algorithms at different activity levels.</p
<p>Accuracy (ACC), positive (PPV) and negative (NPV) predictive values of the tested algorithms.</p
<p>(a) the accuracy comparison of the different methods using the first manually segmented results o...
Accuracy results of MDT1and MDT2 compared to the proposed methods in the test stage, with different ...
Comparison of performance obtained by our approach with other state-of-the-art algorithms.</p
Train and test accuracy for selected classifiers for different projection methods.</p
<p>Comparison of accuracy rate of different features extracted with classification algorithms.</p
<p>• statistically significant degradation</p><p>Accuracy of different algorithms on standard datase...
<p>Results of differential expression analysis of the test data before and after normalization, in c...
Comparative study of test accuracies of ShapAAL model with baseline and state-of-the-art algorithms ...
<p>Results of differential expression analysis of the test data before and after a combination of Co...
<p>Classification accuracy comparison of the proposed research with the state-of-the-art methods.</p
<p>Each data point is obtained by averaging over ten runs, each of which has an independently random...
Quantitative comparison between the state-of-the-art SR algorithms on 3 test datasets.</p
Comparison of accuracy for different approaches, where small value indicates good performance and bo...
Performance statistics of the tested algorithms at different activity levels.</p
<p>Accuracy (ACC), positive (PPV) and negative (NPV) predictive values of the tested algorithms.</p
<p>(a) the accuracy comparison of the different methods using the first manually segmented results o...
Accuracy results of MDT1and MDT2 compared to the proposed methods in the test stage, with different ...
Comparison of performance obtained by our approach with other state-of-the-art algorithms.</p
Train and test accuracy for selected classifiers for different projection methods.</p
<p>Comparison of accuracy rate of different features extracted with classification algorithms.</p
<p>• statistically significant degradation</p><p>Accuracy of different algorithms on standard datase...
<p>Results of differential expression analysis of the test data before and after normalization, in c...
Comparative study of test accuracies of ShapAAL model with baseline and state-of-the-art algorithms ...
<p>Results of differential expression analysis of the test data before and after a combination of Co...
<p>Classification accuracy comparison of the proposed research with the state-of-the-art methods.</p
<p>Each data point is obtained by averaging over ten runs, each of which has an independently random...
Quantitative comparison between the state-of-the-art SR algorithms on 3 test datasets.</p
Comparison of accuracy for different approaches, where small value indicates good performance and bo...
Performance statistics of the tested algorithms at different activity levels.</p
<p>Accuracy (ACC), positive (PPV) and negative (NPV) predictive values of the tested algorithms.</p
<p>(a) the accuracy comparison of the different methods using the first manually segmented results o...
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