<p>The mean detection rate of the six sparse features on different <i>k</i> and <i>ε</i>.</p
Abstract—The paper provides a formal description of the sparsity of a representation via the detecti...
<p>The performances of the different classification algorithms as a function of the number of trials...
The testing accuracies and execution time for six classifiers on different-scale datasets with noise...
<p>Comparison of detection rate using 3 Methods on KITTI and DETRAC datasets.</p
<p>There is only one target item in each attack. Comparison of detection rate when attack size and f...
<p>Comparison of accuracy rate of different features extracted with classification algorithms.</p
<p>Performance of different feature combinations for disease detection and quantification.</p
Assessment of model performance on sparse datasets with different degrees of sparsity (1–10 of 11 fe...
<p>On the left: the number of active features equals 5; in the center: the number of kept parameters...
<p>Mean target detection rates in percent and corresponding standard errors for 3 successive time wi...
<p>Performance indicators of the sparse fusion feature subset and the full feature on different clas...
Comparison of accuracy rates of multi-classification results of different intrusion detection models...
<p>Average detection accuracy across all subjects under different situations.</p
<p>Filter settings were individually optimized for every noise amplitude and step width (data set A)...
<p>The winning frequency is calculated for different feature selection methods for various sizes of ...
Abstract—The paper provides a formal description of the sparsity of a representation via the detecti...
<p>The performances of the different classification algorithms as a function of the number of trials...
The testing accuracies and execution time for six classifiers on different-scale datasets with noise...
<p>Comparison of detection rate using 3 Methods on KITTI and DETRAC datasets.</p
<p>There is only one target item in each attack. Comparison of detection rate when attack size and f...
<p>Comparison of accuracy rate of different features extracted with classification algorithms.</p
<p>Performance of different feature combinations for disease detection and quantification.</p
Assessment of model performance on sparse datasets with different degrees of sparsity (1–10 of 11 fe...
<p>On the left: the number of active features equals 5; in the center: the number of kept parameters...
<p>Mean target detection rates in percent and corresponding standard errors for 3 successive time wi...
<p>Performance indicators of the sparse fusion feature subset and the full feature on different clas...
Comparison of accuracy rates of multi-classification results of different intrusion detection models...
<p>Average detection accuracy across all subjects under different situations.</p
<p>Filter settings were individually optimized for every noise amplitude and step width (data set A)...
<p>The winning frequency is calculated for different feature selection methods for various sizes of ...
Abstract—The paper provides a formal description of the sparsity of a representation via the detecti...
<p>The performances of the different classification algorithms as a function of the number of trials...
The testing accuracies and execution time for six classifiers on different-scale datasets with noise...
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