Usually, performance of classifiers is evaluated on real-world problems that mainly belong to public repositories. However, we ignore the inherent properties of these data and how...
Background: The goal of class prediction studies is to develop rules to accurately predict the class membership of new samples. The rules are derived using the values of the varia...
We address recognition and localization of human actions in realistic scenarios. In contrast to the previous work studying human actions in controlled settings, here we train and ...
In this paper we report about an investigation in which we studied the properties of Bayes' inferred neural network classifiers in the context of outlier detection. The proble...
Background: Overfitting the data is a salient issue for classifier design in small-sample settings. This is why selecting a classifier from a constrained family of classifiers, on...
Jianping Hua, James Lowey, Zixiang Xiong, Edward R...