The need for Bayesian inference arises in military intelligence, medical diagnosis and many other practical applications. The problem is that human inferences are generally conserv...
We propose a new Bayesian approach to object-based image retrieval with relevance feedback. Although estimating the object posterior probability density from few examples seems in...
Derek Hoiem, Rahul Sukthankar, Henry Schneiderman,...
Particle filters (PFs) are Bayesian filters capable of modeling nonlinear, non-Gaussian, and nonstationary dynamical systems. Recent research in PFs has investigated ways to approp...
— Adaptive filtering is normally utilized to estimate system states or outputs from continuous valued observations, and it is of limited use when the observations are discrete e...