We propose a novel semi-supervised classifier for handwritten digit recognition problems that is based on the assumption that any digit can be obtained as a slight transformation...
Abstract. For many statistical pattern recognition methods, distributions of sample vectors are assumed to be normal, and the quadratic discriminant function derived from the proba...
We initiate a novel study of clustering problems. Rather than specifying an explicit objective function to optimize, our framework allows the user of clustering algorithm to speci...
We cope with the metadata recognition in layoutoriented documents. We address the problem as a classification task and propose a method for automatic extraction of relevant featu...
It is well known that, due to illumination effects and the registration/alignment problem, it does not make sense to compare the "values" of two single-pixels for face r...