A novel method to improve the generalization performance of the Minimum Classification Error (MCE) / Generalized Probabilistic Descent (GPD) learning is proposed. The MCE/GPD learn...
Abstract. A representation of a three-dimensional object is autonomously learned from a sequence of the rotating object. The representation consists of single views in form of grap...
Gabriele Peters, Christian Eckes, Christoph von de...
Properly addressing the discretization process of continuos valued features is an important problem during decision tree learning. This paper describes four multi-interval discreti...
This paper presents a probabilistic similarity measure for object recognition from large libraries of line-patterns. We commence from a structural pattern representation which use...
Abstract. Because of its unexpected nature, finding words as equidistant letter sequences (Torah codes) in a text may appear to be interesting. However, there is a significant prob...
Abstract. The increase in accessability to on-line visual data has promoted the interest in browsing and retrieval of images from Image Databases. Current approaches assume either ...
: We present a practical approach to nonparametric cluster analysis of large data sets. The number of clusters and the cluster centres are automatically derived by mode seeking wit...
Abstract. In this paper, we propose a method for recognizing architectural symbols. The method is based on the description of the model through a set of constraints on geometrical ...