- http://stats.org.uk/hmm/
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Image Classification by a Two Dimensional Hidden Markov Model
Jia Li, Amir Najmi and Robert M.Gray
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Training Hidden Markov Models with Multiple Observation - A
Combinatori Method
Xiaolin Li, Member, IEEE Computer Society
CADlink Technology Corporation, 2440 Don Reid Drive, Suite 100,
Ottawa, Ontario, Canada K1H 1E1.
Marc Parizeau,
Member, IEEE Computer Society
Departement de Genie Electrique et de Genie Informatique,
Universite Laval, Ste-Foy, Quebec, Canada G1K 7P4. parizeau@gel.ulaval.ca
and
Rejean Plamondon, Fellow, IEEE
Ecole Polytechnique de Montreal,
Montreal, Quebec, Canada H3C 3A7
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Hidden-Markov-Modelle
Sonja Waldhausen
Biocomputing Group am Fachbereich Mathematik, FU Berlin
Seminar ?uber Bayes’sche Netzwerke
16. Januar 2003
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IEEE TRANSACTIONS ON SPEECH AND AUDIO PROCESSING, VOL. 9, NO. 4, MAY 2001 411
A Modified Baum–Welch Algorithm for Hidden
Markov Models with Multiple Observation Spaces
Paul M. Baggenstoss, Member, IEEE
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Ten years of HMMs
Olivier Capp?e
CNRS, LTCI & ENST, Dpt. TSI
46 rue Barrault, 75634 Paris cedex 13, France.
cappe at tsi.enst.fr
Final version, March 12 2001
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Soft Computing 6 (2002) 400 – 405 Springer-Verlag 2002
DOI 10.1007/s00500-002-0192-8
Perception-based hidden Markov models: a theoretical framework
for data mining and knowledge discovery
T. D. Pham
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Gaussian Observation Hidden Markov models for
EEG analysis
William D. Penny and Stephen J. Roberts
Technical Report,
Neural Systems Research Group,
Department of Electrical and Electronic Engineering,
Imperial College of Science, Technology and Medicine,
London SW7 2BT., U.K.
October 5, 1998
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Information Extraction with HMMs and Shrinkage
Dayne Freitag
Andrew Kachites McCallum
Just Research
4616 Henry Street
Pittsburgh, PA 15213
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AN HMM APPROACH TO ADAPTIVE DEMODULATION OF QAM SIGNALS IN FADING CHANNELS
I. B. COLLINGS AND J. B. MOORE
Department of Systems Engineering, Research School of Information Science and Engineering,
Australian National University, Canberra 0200, Australia
Int. Jour. of Adaptive Cont. and Signal Proc., Vol. 8, No. 5, pp. 457474, Oct. 1994
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A Bayesian Computer Vision System
for Modeling Human Interactions
Nuria Oliver , Barbara Rosario and Alex Pentland
Vision and Modeling. Media Laboratory, MIT,
Cambridge, MA 02139, USA
http://nuria.www.media.mit.edu/¸nuria/humanBehavior/humanBehavior.html
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Recognition of Head Gestures Using Hidden Markov Models
Carlos Morimoto, Yaser Yacoob, Larry Davis
Computer Vision Laboratory, Center for Automation Research
University of Maryland, College Park, MD 20742
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Markov Random Field Models
in Computer Vision
S. Z. Li
School of Electrical and Electronic Engineering
Nanyang Technological University, Singapore 2263
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A HIDDEN MARKOV MODEL BASED FRAMEWORK FOR RECOGNITION OF HUMANS
FROM GAIT SEQUENCES
Aravind Sundaresan, Amit Roy Chowdhury, Rama Chellappa
Centre for Automation Research, and Department of Electrical and Computer Engineering
University of Maryland, College Park, MD 20742
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Complexity of Comparing Hidden Markov Models
Rune B. Lyngsø and Christian N. S. Pedersen
Baskin Center for Computer Science and Engineering, University of California,
BiRC # # # , Department of Computer Science, University of Aarhus, Ny Munkegade
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