Adaptor grammars (Johnson et al., 2007b) are a non-parametric Bayesian extension of Probabilistic Context-Free Grammars (PCFGs) which in effect learn the probabilities of entire s...
In the traditional mixture of Gaussians background model, the generating process of each pixel is modeled as a mixture of Gaussians over color. Unfortunately, this model performs ...
Two main issues arise when working in the area of texture segmentation: the need to describe the texture accurately by capturing its underlying structure, and the need to perform ...
This paper focuses on a solution to better adapt ASR systems, whose language models (LM) are usually trained on topic-independent corpora, to new topics, in particular in the case...
Microarray gene expression image analysis is a labor-intensive task and requires human intervention since microarray images are contaminated with noise and artifacts while spots a...