This paper proposes a new approach for classifying multivariate time-series with applications to the problem of writer independent online handwritten character recognition. Each t...
Background: Kernel-based learning algorithms are among the most advanced machine learning methods and have been successfully applied to a variety of sequence classification tasks ...
Peter Meinicke, Maike Tech, Burkhard Morgenstern, ...
Using variational analysis, we study the linear regularity for a collection of finitely many closed sets. In particular, we extend duality characterizations of the linear regularit...
Fluorescence microscope images capture information from an entire field of view, which often comprises several cells scattered on the slide. We have previously trained classifiers...
– This paper presents an ongoing investigation to select optimal subset of features from set of well-known myoelectric signals (MES) features in time and frequency domains. Four ...