This paper presents a novel texture segmentation method using Bayesian estimation and neural networks. Multi-scale wavelet coefficients and the context information extracted from n...
We present a technique which complements Hidden Markov Models by incorporating some lexicalized states representing syntactically uncommon words. 'Our approach examines the d...
This paper applies two dynamic Bayes networks that include theoretical and measured kinematic features of the vocal tract, respectively, to the task of labeling phoneme sequences ...
We describe a generative model of the relationship between two images. The model is defined as a factored threeway Boltzmann machine, in which hidden variables collaborate to de...
Joshua Susskind, Roland Memisevic, Geoffrey Hinton...
Abstract. Natural scenes consist of a wide variety of stochastic patterns. While many patterns are represented well by statistical models in two dimensional regions as most image s...