This paper presents a new framework called fuzzy relevance feedback in interactive content-based image retrieval (CBIR) systems based on soft-decision. An efficient learning appro...
The paper considers an interactive search paradigm in which at each round a user is presented with a set of k images and is required to select one that is closest to her target. P...
In this paper, we present a long term learning system for content based image retrieval over a network. Relevant feedback is used among different sessions to learn both the simila...
We introduce in this paper the general architecture of an image search engine based on pre-attentive similarities. The components of this system are presented and some of them are...
Alexander Heinrichs, Dimitri Koubaroulis, Barbara ...
Relevance feedback is an important mechanism for narrowing the semantic gap in content-based image retrieval and the process involves the user labeling positive and negative images...