FIRE in ImageCLEF 2007.
Thomas Deselaers, Tobias Gass, Tobias Weyand, Hermann Ney · CLEF (Working Notes) · 2007
We present the methods we applied in the four dierent tasks of the ImageCLEF 2007 content-based image retrieval evaluation. We participated in all four tasks using a variety of methods. Global and local image descriptors are applied using nearest neighbour search for the medical and photo retrieval tasks and discriminative models for the object retrieval and the medical automatic annotation task. For the photo and medical retrieval task, we apply a maximum entropy training method to learn an optimal feature weighting from the queries and qrels from last year. This method works particularly well if the queries are very similar as they were in the medical retrieval task.