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ICIP
2007
IEEE
15 years 8 months ago
Modeling vs. Segmenting Images Using A Probabilistic Approach
Image segmentation is conventionally formulated as a pixellabeling problem, in which “hard” decisions have to be made to partition pixels into regions. As image segmentation i...
Datong Chen
CHES
2006
Springer
81views Cryptology» more  CHES 2006»
15 years 5 months ago
Template Attacks in Principal Subspaces
Side-channel attacks are a serious threat to implementations of cryptographic algorithms. Secret information is recovered based on power consumption, electromagnetic emanations or ...
Cédric Archambeau, Eric Peeters, Fran&ccedi...
WSC
1998
15 years 3 months ago
Bayesian Model Selection when the Number of Components is Unknown
In simulation modeling and analysis, there are two situations where there is uncertainty about the number of parameters needed to specify a model. The first is in input modeling w...
Russell C. H. Cheng
154
Voted
CAIP
2001
Springer
293views Image Analysis» more  CAIP 2001»
15 years 6 months ago
A Markov Random Field Image Segmentation Model Using Combined Color and Texture Features
In this paper, we propose a Markov random field (MRF) image segmentation model which aims at combining color and texture features. The theoretical framework relies on Bayesian est...
Zoltan Kato, Ting-Chuen Pong
117
Voted
ECCV
2008
Springer
16 years 4 months ago
Regular Texture Analysis as Statistical Model Selection
An approach to the analysis of images of regular texture is proposed in which lattice hypotheses are used to define statistical models. These models are then compared in terms of t...
Junwei Han, Stephen J. McKenna, Ruixuan Wang