This paper presents a medical image retrieval framework that uses visual concepts in a feature space employing statistical models built using a probabilistic multi-class support v...
Md. Mahmudur Rahman, Sameer Antani, George R. Thom...
We propose a novel Bayesian learning framework of hierarchical mixture model by incorporating prior hierarchical knowledge into concept representations of multi-level concept struc...
This paper describes a content-based image retrieval system that employs both higher-level and lower-level vision methodologies separately and in conjunction for the retrieval of ...
We have developed a novel system for content-based image retrieval in large, unannotated databases. The system is called PicSOM, and it is based on tree structured self-organizing...
Jorma Laaksonen, Markus Koskela, Sami Laakso, Erkk...
We explore the application of a graph representation to model similarity relationships that exist among images found on the Web. The resulting similarity-induced graph allows us t...
Barbara Poblete, Benjamin Bustos, Marcelo Mendoza,...