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» Minimum Message Length Hidden Markov Modelling
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PR
2010
147views more  PR 2010»
13 years 4 months ago
Minimum classification error learning for sequential data in the wavelet domain
Wavelet analysis has found widespread use in signal processing and many classification tasks. Nevertheless, its use in dynamic pattern recognition have been much more restricted ...
D. Tomassi, Diego H. Milone, L. Forzani
ICML
2002
IEEE
14 years 7 months ago
Univariate Polynomial Inference by Monte Carlo Message Length Approximation
We apply the Message from Monte Carlo (MMC) algorithm to inference of univariate polynomials. MMC is an algorithm for point estimation from a Bayesian posterior sample. It partiti...
Leigh J. Fitzgibbon, David L. Dowe, Lloyd Allison
MMSEC
2005
ACM
147views Multimedia» more  MMSEC 2005»
13 years 12 months ago
A Bayesian image steganalysis approach to estimate the embedded secret message
Image steganalysis so far has dealt only with detection of a hidden message and estimation of some of its parameters (e.g., message length and secret key). To our knowledge, so fa...
Aruna Ambalavanan, Rajarathnam Chandramouli
TASLP
2011
13 years 1 months ago
A Probabilistic Interaction Model for Multipitch Tracking With Factorial Hidden Markov Models
—We present a simple and efficient feature modeling approach for tracking the pitch of two simultaneously active speakers. We model the spectrogram features of single speakers u...
Michael Wohlmayr, Michael Stark, Franz Pernkopf
AUSAI
2009
Springer
14 years 1 months ago
Information-Theoretic Image Reconstruction and Segmentation from Noisy Projections
The minimum message length (MML) principle for inductive inference has been successfully applied to image segmentation where the images are modelled by Markov random fields (MRF)....
Gerhard Visser, David L. Dowe, Imants D. Svalbe