This paper presents adaptive weighting method for combining local classifiers by particle filter. In recent years, the effectiveness of combination of local classifiers (features)...
We propose a well-founded method of ranking a pool of m trained classifiers by their suitability for the current input of n instances. It can be used when dynamically selecting a s...
Most of what we know about multiple classifier systems is based on empirical findings, rather than theoretical results. Although there exist some theoretical results for simple and...
Abstract. This paper introduces a new method to determine appealing placements of textual annotations for complex-shaped geometric models. It employs dynamic potential fields, whi...