We show that it is possible to extend hidden Markov models to have a countably infinite number of hidden states. By using the theory of Dirichlet processes we can implicitly integ...
Matthew J. Beal, Zoubin Ghahramani, Carl Edward Ra...
Standard hidden Markov models (HMM's) have been studied extensively in the last two decades. It is well known that these models assume state conditional independence of the ob...
We present the use of layered probabilistic representations for modeling human activities, and describe how we use the representation to do sensing, learning, and inference at mul...
This paper presents a new approach for Handwritten Word Recognition based on Hidden Markov Model theory and the sliding window technique. The new approach uses specific singularit...
Sebastiano Impedovo, Anna Ferrante, Raffaele Modug...