We build a comprehensive macro-learning system and contribute in three different dimensions that have previously not been addressed adequately. Firstly, we learn macro-sets conside...
This paper gives an overview of recent approaches towards image representation and image similarity computation for content-based image retrieval and automatic image annotation (ca...
Abstract. We present a logical approach to graph theoretical learning that is based on using alphabetic substitutions for modelling graph morphisms. A classi ed graph is represente...
Visual interpretation of events requires both an appropriate representation of change occurring in the scene and the application of semantics for differentiating between different...
Which one comes first: segmentation or recognition? We propose a unified framework for carrying out the two simultaneously and without supervision. The framework combines a fle...