— Many image compression techniques require the quantization of multiple vector sources with significantly different distributions. With vector quantization (VQ), these sources ...
Scaling up document-image classifiers to handle an unlimited variety of document and image types poses serious challenges to conventional trainable classifier technologies. Highly...
In this paper, we present a prototype that helps visualizing the relative importance of sentences extracted from medical texts using Embodied Conversational Agents (ECA). We propo...
People are thirsty for medical information. Existing Web search engines often cannot handle medical search well because they do not consider its special requirements. Often a medi...
Abstract. We propose an algorithm for Sparse Bayesian Classification for multi-class problems using Automatic Relevance Determination(ARD). Unlike other approaches which treat mult...