Conventional approaches to image retrieval are based on the assumption that relevant images are physically near the query image in some feature space. This is the basis of the clu...
Retrieving information from heterogeneous data sources in a flexible manner and within a single (database) framework is still a challenge. In this paper we present several extensi...
We introduce a new model for semantic annotation and retrieval from image databases. The new model is based on a probabilistic formulation that poses annotation and retrieval as c...
With the growing popularity of information retrieval (IR) in distributed systems and in particular P2P Web search, a huge number of protocols and prototypes have been introduced i...
Thomas Neumann, Matthias Bender, Sebastian Michel,...
In this paper, we propose a novel transductive learning framework named manifold-ranking based image retrieval (MRBIR). Given a query image, MRBIR first makes use of a manifold ra...