Abstract. A tracking-by-detection framework is proposed that combines nearest-neighbor classification of bags of features, efficient subwindow search, and a novel feature selection...
To obtain classification systems with both good generalizat`ion performance and efficiency in space and time, we propose a learning method based on combinations of weak classifiers...
In this paper, a framework for the analysis of the error-reject trade-off in linearly combined classifiers is proposed. We start from a framework developed by Tumer and Ghosh [1,2...
Abstract Investigating a data set of the critical size makes a classification task difficult. Studying dissimilarity data refers to such a problem, since the number of samples equa...
Elzbieta Pekalska, Marina Skurichina, Robert P. W....
We consider a supervised learning setting in which the main cost of learning is the number of training labels and one can obtain a single label for a bag of examples, indicating o...