We discuss the issues and challenges of generic object recognition. We argue that high-level, volumetric part-based descriptions are essential in the process of recognizing object...
The perplexing effects of noise and high feature dimensionality greatly complicate functional magnetic resonance imaging (fMRI) classification. In this paper, we present a novel f...
Mean shift clustering is a powerful unsupervised data
analysis technique which does not require prior knowledge
of the number of clusters, and does not constrain the shape
of th...
In this paper we propose to use lexical semantic networks to extend the state-of-the-art object recognition techniques. We use the semantics of image labels to integrate prior kno...
Closing the semantic gap in content based image retrieval (CBIR) basically requires the knowledge of the user's intention which is usually translated into a sequence of quest...