This paper describes a hierarchical Bayesian network used for segmenting desert images and detecting off road drivable corridors for autonomous navigation. Unlike the embedded hid...
We present a learning algorithm for non-parametric hidden Markov models with continuous state and observation spaces. All necessary probability densities are approximated using sa...
We introduce in this paper a generalization of the widely used hidden Markov models (HMM's), which we name "structural hidden Markov models" (SHMM). Our approach is ...
Hidden Markov models (HMMs) have received considerable attention in various communities (e.g, speech recognition, neurology and bioinformatic) since many applications that use HMM...
Hidden Markov chains (HMC) are widely applied in various problems occurring in different areas like Biosciences, Climatology, Communications, Ecology, Econometrics and Finances, ...