A novel dynamic multi-model relevance feedback procedure for content-based image retrieval

This novel procedure has been tested in a collection with a large semantic gap, the Wikipedia collection. Two types of experiments have been performed, one with an automatic user and another with a typical user. The method is compared to some recent similar approaches in literature, obtaining very good performance in terms of the MAP evaluation measure.