Multi-label learning deals with ambiguous examples each may belong to several concept classes simultaneously. In this learning framework, the inherent ambiguity of each example is...
AI problems such as autonomous robotic exploration, automatic diagnosis and activity recognition have in common the need for choosing among a set of informative but possibly expen...
Abstract. Automatic pattern classifiers that allow for on-line incremental learning can adapt internal class models efficiently in response to new information without retraining fr...
Abstract. Gabor filters have demonstrated their effectiveness in automatic face recognition. However, one drawback of Gabor-based face representations is the huge amount of data th...
Most new words, or neologisms, bubble beneath the surface of widespread usage for some time, perhaps even years, before gaining acceptance in conventional print dictionaries [1]. A...