<p>(a) Classification rates for gender difference computed from a support vector machine classifier with a ten-fold cross validation method on PCs sorted by effect size for younger and older subject subgroups. (b) Effect sizes of all PCs computed from younger and older subject subgroups for gender difference.</p
Histograms representing the distribution of male and female participants across the age range for bo...
Automatic age and gender recognition for speech applications is very important for a number of reaso...
<p>The frequency distributions among gender in patients with type 2 diabetes and control groups stra...
<p>(a) Classification rates for gender difference computed from a support vector machine classifier ...
<p>The results show that irrespective of the gender of the participants, the accuracy for female sti...
<p>Women are reference-group.* Indicates a statistically significant (p<0.05) sex difference in the ...
Support Vector Machines (SVMs) are investigated for visual gender classification with low-resolution...
<p>Criteria for comparing models with different number of classes for gender-based discrimination us...
<p>Data are n (%) for diagnoses, mean age (range) and the female (F)/male (M) distribution percentag...
This report presents gender classification based on facial images using dimensionality reduction tec...
<p>Univariate GLM for age-groups separately, showing age and gender main effects on gmCMRO<sub>2</su...
<p>Mean age of misclassified subjects in AD and control group using SVM classification with (middle ...
Each row shows median gender homophily across all fields and years, marginal effect of trainee and m...
Previous studies have shown that machine-learning (ML) algorithms can “predict” sex based on brain a...
<p>Neuropsychology Data and Between-Groups Comparisons: ANCOVAs (controlling for age differences) of...
Histograms representing the distribution of male and female participants across the age range for bo...
Automatic age and gender recognition for speech applications is very important for a number of reaso...
<p>The frequency distributions among gender in patients with type 2 diabetes and control groups stra...
<p>(a) Classification rates for gender difference computed from a support vector machine classifier ...
<p>The results show that irrespective of the gender of the participants, the accuracy for female sti...
<p>Women are reference-group.* Indicates a statistically significant (p<0.05) sex difference in the ...
Support Vector Machines (SVMs) are investigated for visual gender classification with low-resolution...
<p>Criteria for comparing models with different number of classes for gender-based discrimination us...
<p>Data are n (%) for diagnoses, mean age (range) and the female (F)/male (M) distribution percentag...
This report presents gender classification based on facial images using dimensionality reduction tec...
<p>Univariate GLM for age-groups separately, showing age and gender main effects on gmCMRO<sub>2</su...
<p>Mean age of misclassified subjects in AD and control group using SVM classification with (middle ...
Each row shows median gender homophily across all fields and years, marginal effect of trainee and m...
Previous studies have shown that machine-learning (ML) algorithms can “predict” sex based on brain a...
<p>Neuropsychology Data and Between-Groups Comparisons: ANCOVAs (controlling for age differences) of...
Histograms representing the distribution of male and female participants across the age range for bo...
Automatic age and gender recognition for speech applications is very important for a number of reaso...
<p>The frequency distributions among gender in patients with type 2 diabetes and control groups stra...