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ECCV
1994
Springer
14 years 1 months ago
Markov Random Field Models in Computer Vision
A variety of computer vision problems can be optimally posed as Bayesian labeling in which the solution of a problem is dened as the maximum a posteriori (MAP) probability estimate...
Stan Z. Li
IJCNN
2000
IEEE
14 years 14 days ago
Competing Hidden Markov Models on the Self-Organizing Map
This paper presents an unsupervised segmentation method for feature sequences based on competitivelearning hidden Markov models. Models associated with the nodes of the Self-Organ...
Panu Somervuo
ICIP
2010
IEEE
13 years 6 months ago
A non-stationary Hidden Markov Model of multiview video traffic
Multiview video is increasingly getting attention due to emerging applications such as 3DTV and immersive teleconferencing. In this paper, we present a non-stationary Hidden Marko...
Lorenzo Rossi, Jacob Chakareski, Pascal Frossard, ...
PAKDD
2009
ACM
126views Data Mining» more  PAKDD 2009»
14 years 3 months ago
Tree-Based Method for Classifying Websites Using Extended Hidden Markov Models
One important problem proposed recently in the field of web mining is website classification problem. The complexity together with the necessity to have accurate and fast algorit...
Majid Yazdani, Milad Eftekhar, Hassan Abolhassani

Book
5396views
15 years 7 months ago
Markov Random Field Modeling in Computer Vision
Markov random field (MRF) theory provides a basis for modeling contextual constraints in visual processing and interpretation. It enables us to develop optimal vision algorithms sy...
Stan Z. Li