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NIPS
2001
15 years 3 months ago
Bayesian time series classification
This paper proposes an approach to classification of adjacent segments of a time series as being either of classes. We use a hierarchical model that consists of a feature extract...
Peter Sykacek, Stephen J. Roberts
129
Voted
LCN
2000
IEEE
15 years 6 months ago
Nonlinear Time-Series Model for VBR Video Traffic
In this paper, variable bit rate (VBR) H.261 encoded video traffic is modeled by a nonlinear time series process. A threshold autoregressive (TAR) process is of particular interes...
Jimmie L. Davis, Kavitha Chandra, Charles Thompson
ICDAR
2003
IEEE
15 years 7 months ago
Automatic Classification of Hand Drawn Geometric Shapes using Constructional Sequence Analysis
A method for automatically assessing the constructional sequence from a neuropsychological drawing task using Hidden Markov Models is presented. We also present a method of extrac...
Richard M. Guest, Samuel Chindaro, Michael C. Fair...
128
Voted
CVPR
1999
IEEE
16 years 3 months ago
Time-Series Classification Using Mixed-State Dynamic Bayesian Networks
We present a novel mixed-state dynamic Bayesian network (DBN) framework for modeling and classifying timeseries data such as object trajectories. A hidden Markov model (HMM) of di...
Vladimir Pavlovic, Brendan J. Frey, Thomas S. Huan...
122
Voted
ICIP
2001
IEEE
16 years 3 months ago
A comparison of discrete and continuous output modeling techniques for a pseudo-2D hidden Markov model face recognition system
Face recognition has become an important topic within the field of pattern recognition and computer vision. In this field a number of different approaches to feature extraction, m...
Frank Wallhoff, Stefan Eickeler, Gerhard Rigoll