We develop a hierarchical, nonparametric statistical model for wavelet representations of natural images. Extending previous work on Gaussian scale mixtures, wavelet coefficients ...
Jyri J. Kivinen, Erik B. Sudderth, Michael I. Jord...
An ideal shape model should be both invariant to global transformations and robust to local distortions. In this paper we present a new shape modeling framework that achieves both...
We address the feature selection problem for hidden Markov models (HMMs) in sequence classification. Temporal correlation in sequences often causes difficulty in applying featur...
Pei Yin, Irfan A. Essa, Thad Starner, James M. Reh...
This work introduces a Hidden Markov Model (HMM) based technique to classify agricultural crops. The method recognizes different crops by analyzing their spectral profiles over a ...
P. B. C. Leite, Raul Queiroz Feitosa, A. R. Formag...
Hidden Markov Models (HMMs) provide a simple and effective framework for modelling time-varying spectral vector sequences. As a consequence, almost all present day large vocabula...