This paper describes an ongoing project which seeks to contribute to a wider understanding of the realities of bridging the semantic gap in visual image retrieval. A comprehensive ...
Peter G. B. Enser, Christine J. Sandom, Paul H. Le...
In this paper, we propose a novel approach of image annotation by constructing a hierarchical mapping between lowlevel visual features and text features utilizing the relations wi...
Libraries have traditionally used manual image annotation for indexing and then later retrieving their image collections. However, manual image annotation is an expensive and labo...
The automatic annotation of images presents a particularly complex problem for machine learning researchers. In this work we experiment with semantic models and multi-class learnin...
We propose a novel Bayesian learning framework of hierarchical mixture model by incorporating prior hierarchical knowledge into concept representations of multi-level concept struc...