The Fisher kernel is a generic framework which combines the benefits of generative and discriminative approaches to pattern classification. In this contribution, we propose to a...
We try to link elastic matching with a statistical discrimination framework to overcome the overfitting problem which often degrades the performance of elastic matchingbased onli...
—Classification has been used for modeling many kinds of data sets, including sets of items, text documents, graphs, and networks. However, there is a lack of study on a new kind...
In this paper, we present an extension of PHIL, a declarative language for filtering information from XML data. The proposed approach allows us to extract relevant data as well a...
Cascades of classifiers constitute an important architecture for fast object detection. While boosting of simple (weak) classifiers provides an established framework, the design of...