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COR
2008
116views more  COR 2008»
13 years 7 months ago
Supply disruptions with time-dependent parameters
We consider a firm that faces random demand and receives product from a single supplier who faces random supply. The supplier's availability may be affected by events such as...
Andrew M. Ross, Ying Rong, Lawrence V. Snyder
ICCV
2003
IEEE
14 years 9 months ago
Recognition of Group Activities using Dynamic Probabilistic Networks
Dynamic Probabilistic Networks (DPNs) are exploited for modelling the temporal relationships among a set of different object temporal events in the scene for a coherent and robust...
Shaogang Gong, Tao Xiang
ICIP
2006
IEEE
14 years 9 months ago
A Profile Hidden Markov Model Framework for Modeling and Analysis of Shape
In this paper we propose a new framework for modeling 2D shapes. A shape is first described by a sequence of local features (e.g., curvature) of the shape boundary. The resulting ...
Rui Huang, Vladimir Pavlovic, Dimitris N. Metaxas
ICC
2007
IEEE
135views Communications» more  ICC 2007»
14 years 1 months ago
New Results on Single-Step Power Control System in Finite State Markov Channel: Power Control Error Modelling and Queueing Varia
— The analysis regarding the impact of the single-step power control (SSPC) scheme on the system performance such as bit error rate, packet error rate and queueing variation is h...
Shi-Yong Lee, Min-Kuan Chang
ICIP
2001
IEEE
14 years 9 months ago
EM algorithms of Gaussian mixture model and hidden Markov model
The HMM (Hidden Markov Model) is a probabilistic model of the joint probability of a collection of random variables with both observations and states. The GMM (Gaussian Mixture Mo...
Guorong Xuan, Wei Zhang, Peiqi Chai