Background: Classification and variable selection play an important role in knowledge discovery in highdimensional data. Although Support Vector Machine (SVM) algorithms are among...
Natalia Becker, Grischa Toedt, Peter Lichter, Axel...
We propose a novel learning algorithm to detect moving pedestrians from a stationary camera in real-time. The algorithm learns a discriminative model based on eigenflow, i.e. the ...
Instance selection and feature selection are two orthogonal methods for reducing the amount and complexity of data. Feature selection aims at the reduction of redundant features i...
We demonstrate a phonotactic-semantic paradigm for spoken document categorization. In this framework, we define a set of acoustic words instead of lexical words to represent acous...
Automated text categorization is an important technique for many web applications, such as document indexing, document filtering, and cataloging web resources. Many different appr...