Abstract. The paper presents new method for sequential classification of the time series observations. Methods and algorithms of sequential recognition are obtained on the basis of...
Hierarchical clustering methods are important in many data mining and pattern recognition tasks. In this paper we present an efficient coarse grained parallel algorithm for Single...
This paper describes an incremental approach to parsing transcribed spontaneous speech containing disfluencies with a Hierarchical Hidden Markov Model (HHMM). This model makes use...
We describe an algorithm for automatically learning discriminative components of objects with SVM classifiers. It is based on growing image parts by minimizing theoretical bounds ...
Bernd Heisele, Thomas Serre, Massimiliano Pontil, ...
Abstract. We present a large-scale Neuromorphic model based on integrateand-fire (IF) neurons that analyses objects and their depth within a moving visual scene. A feature-based al...