An important problem in image labeling concerns learning with images labeled at varying levels of specificity. We propose an approach that can incorporate images with labels drawn...
In this paper, we propose a novel framework for face super-resolution based on a layered predictor network. In the first layer, multiple predictors are trained online with a dynami...
Abstract. We introduce a non-linear shape prior for the deformable model framework that we learn from a set of shape samples using recent manifold learning techniques. We model a c...
Abstract. This paper presents the overall system of a learning, selforganizing, and adaptive controller used to optimize the combustion process in a hard-coal fired power plant. T...
Erik Schaffernicht, Volker Stephan, Klaus Debes, H...
This paper proposes novel hierarchical self-organizing associative memory architecture for machine learning. This memory architecture is characterized with sparse and local interco...