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» Supervised Image Segmentation Using Markov Random Fields
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JMLR
2010
191views more  JMLR 2010»
13 years 25 days ago
Noise-contrastive estimation: A new estimation principle for unnormalized statistical models
We present a new estimation principle for parameterized statistical models. The idea is to perform nonlinear logistic regression to discriminate between the observed data and some...
Michael Gutmann, Aapo Hyvärinen
CAIP
2009
Springer
202views Image Analysis» more  CAIP 2009»
13 years 3 months ago
Near-Regular Texture Synthesis
This paper describes a method for seamless enlargement or editing of difficult colour textures containing simultaneously both regular periodic and stochastic components. Such textu...
Michal Haindl, Martin Hatka
ICDAR
2007
IEEE
14 years 11 days ago
Energy-Based Models in Document Recognition and Computer Vision
The Machine Learning and Pattern Recognition communities are facing two challenges: solving the normalization problem, and solving the deep learning problem. The normalization pro...
Yann LeCun, Sumit Chopra, Marc'Aurelio Ranzato, Fu...
ECCV
2006
Springer
14 years 8 months ago
Tracking Dynamic Near-Regular Texture Under Occlusion and Rapid Movements
We present a dynamic near-regular texture (NRT) tracking algorithm nested in a lattice-based Markov-Random-Field (MRF) model of a 3D spatiotemporal space. One basic observation use...
Wen-Chieh Lin, Yanxi Liu
TMI
2008
136views more  TMI 2008»
13 years 6 months ago
Classification of fMRI Time Series in a Low-Dimensional Subspace With a Spatial Prior
We propose a new method for detecting activation in functional magnetic resonance imaging (fMRI) data. We project the fMRI time series on a low-dimensional subspace spanned by wave...
François G. Meyer, Xilin Shen