Information retrieval is an empirical science; the field cannot move forward unless there are means of evaluating the innovations devised by researchers. However the methodologies...
Mark Sanderson, Martin Braschler, Nicola Ferro, Ju...
Background: The study of biological systems demands computational support. If targeting a biological problem, the reuse of existing computational models can save time and effort. ...
Ron Henkel, Lukas Endler, Andre Peters, Nicolas Le...
We address the challenge of semantic gap reduction for image retrieval through an improved SVM-based active relevance feedback framework, together with a hybrid visual and concept...
In Content-based Image Retrieval (CBIR), accurately ranking the returned images is of paramount importance, since users consider mostly the topmost results. The typical ranking st...
Fabio F. Faria, Adriano Veloso, Humberto Mossri de...
Image retrieval critically relies on the distance function used to compare a query image to images in the database. We suggest to learn such distance functions by training binary ...