Deterministic gate delay models have been widely used to find the transition probabilities at the nodes of a circuit for calculating the power dissipation. However, with progress...
Abstract. The Bayesian approach to machine learning amounts to inferring posterior distributions of random variables from a probabilistic model of how the variables are related (th...
This paper presents a novel feature based parameterization approach of human bodies from the unorganized cloud points and the parametric design method for generating new models ba...
In this paper we present an opinion summarization technique in spoken dialogue systems. Opinion mining has been well studied for years, but very few have considered its applicatio...
We present a Bayesian framework for content-based image retrieval which models the distribution of color and texture features within sets of related images. Given a userspecified ...