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» TCP Traffic Classification Using Markov Models
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AVSS
2007
IEEE
14 years 1 months ago
Vehicular traffic density estimation via statistical methods with automated state learning
This paper proposes a novel approach of combining an unsupervised clustering scheme called AutoClass with Hidden Markov Models (HMMs) to determine the traffic density state in a R...
Evan Tan, Jing Chen
ICIP
2003
IEEE
14 years 9 months ago
Unsupervised Bayesian image segmentation using wavelet-domain hidden Markov models
In this paper, we study unsupervised image segmentation using wavelet-domain hidden Markov models (HMMs). We first review recent supervised Bayesian image segmentation algorithms ...
X. Song, G. Fan
CVPR
2009
IEEE
15 years 2 months ago
Contextual Classification with Functional Max-Margin Markov Networks
We address the problem of label assignment in computer vision: given a novel 3-D or 2-D scene, we wish to assign a unique label to every site (voxel, pixel, superpixel, etc.). To...
Daniel Munoz, James A. Bagnell, Martial Hebert, Ni...
CN
2004
103views more  CN 2004»
13 years 7 months ago
Modeling IP traffic: joint characterization of packet arrivals and packet sizes using BMAPs
This paper proposes a traffic model and a parameter fitting procedure that are capable of achieving accurate prediction of the queuing behavior for IP traffic exhibiting long-rang...
Paulo Salvador, António Pacheco, Rui Valada...
TON
2010
167views more  TON 2010»
13 years 2 months ago
A Machine Learning Approach to TCP Throughput Prediction
TCP throughput prediction is an important capability in wide area overlay and multi-homed networks where multiple paths may exist between data sources and receivers. In this paper...
Mariyam Mirza, Joel Sommers, Paul Barford, Xiaojin...