Abstract. We study discriminative joint density models, that is, generative models for the joint density p(c, x) learned by maximizing a discriminative cost function, the condition...
In this paper, we investigate a simple, mistakedriven learning algorithm for discriminative training of continuous density hidden Markov models (CD-HMMs). Most CD-HMMs for automat...
Seeing biological motion is very important for both humans and computers. Psychophysics experiments show that the ability of our visual system for biological motion detection and ...
Metal and beam-hardening artifacts are tough issues in Computed Tomography (CT) images. This paper proposes an iterative Maximum A Posteriori (MAP) reconstruction algorithm aiming...
We consider the problem of predicting a sequence of real-valued multivariate states from a given measurement sequence. Its typical application in computer vision is the task of mo...