The classical probabilistic models attempt to capture the Ad hoc information retrieval problem within a rigorous probabilistic framework. It has long been recognized that the prim...
Recent research in automated learning has focused on algorithms that learn from a combination of tagged and untagged data. Such algorithms can be referred to as semi-supervised in...
The surface growing framework presented by Besl and Jain [2] has served as the basis for many range segmentation techniques. It has been augmented with alternative fitting techni...
— We present a general approach for the hierarchical segmentation and labeling of document layout structures. This approach models document layout as a grammar and performs a glo...
In this paper we propose the Local Credibility Concept (LCC), a novel technique for incremental classifiers. It measures the classification rate of the classifier’s local mod...