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» TCP Traffic Classification Using Markov Models
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AVSS
2007
IEEE
15 years 10 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
16 years 6 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
16 years 11 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»
15 years 4 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»
14 years 11 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...