We study the problem of learning to rank images for image retrieval. For a noisy set of images indexed or tagged by the same keyword, we learn a ranking model from some training e...
The present work aims at discovering new associations between medical concepts to be exploited as input in retrieval and indexing. Material and Methods: Association rules method is...
This paper presents a novel platform for image retrieval based on a two-level architecture inspired from human cognitive mechanisms. These two levels provide both generic similari...
John Moustakas, Kostas Marias, Socrates Dimitriadi...
We consider the problem of learning a mapping function from low-level feature space to high-level semantic space. Under the assumption that the data lie on a submanifold embedded ...
In this paper, we propose an iterative similarity propagation approach to explore the inter-relationships between Web images and their textual annotations for image retrieval. By ...