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» Markov Random Field Modeling in Computer Vision
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ICML
2001
IEEE
14 years 9 months ago
Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data
We present conditional random fields, a framework for building probabilistic models to segment and label sequence data. Conditional random fields offer several advantages over hid...
John D. Lafferty, Andrew McCallum, Fernando C. N. ...
CVPR
2008
IEEE
14 years 11 months ago
Learning coupled conditional random field for image decomposition with application on object categorization
This paper proposes a computational system of object categorization based on decomposition and adaptive fusion of visual information. A coupled Conditional Random Field is develop...
Xiaoxu Ma, W. Eric L. Grimson
ICPR
2004
IEEE
14 years 10 months ago
Unsupervised Image Segmentation Using A Simple MRF Model with A New Implementation Scheme
A Markov random field (MRF) model with a new implementation scheme is proposed for unsupervised image segmentation based on image features. The traditional two-component MRF model...
David A. Clausi, Huawu Deng
VISAPP
2010
13 years 6 months ago
Hierarchical Conditional Random Field for Multi-class Image Classification
Michael Ying Yang, Wolfgang Förstner, Martin ...
ICIP
2007
IEEE
14 years 3 months ago
Fast Blotch Detection Algorithm for Degraded Film Sequences Based on MRF Models
This paper proposes a fast blotch detection algorithm based on a Markov Random Field (MRF) model with less computational load and with lower false alarm rate than the existing MRF...
Sang-Churl Nam, Masahide Abe, Masayuki Kawamata