There is growing interest in applying Bayesian techniques to NLP problems. There are a number of different estimators for Bayesian models, and it is useful to know what kinds of t...
This paper is concerned with joint Bayesian endmember extraction and linear unmixing of hyperspectral images using a spatial prior on the abundance vectors. We hypothesize that hy...
This study focuses on the segmentation and characterization of oil slicks on the sea surface from synthetic aperture radar (SAR) observations. In fact, an increase in viscosity du...
We investigate the problem of acoustic modeling in which prior language-specific knowledge and transcribed data are unavailable. We present an unsupervised model that simultaneou...
This paper presents a new approach to scene analysis, which aims at extracting structured information from a video sequence using directly low-level data. The method models the se...