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» Efficient Learning to Label Images
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130
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SIAMIS
2010
378views more  SIAMIS 2010»
14 years 4 months ago
Global Interactions in Random Field Models: A Potential Function Ensuring Connectedness
Markov random field (MRF) models, including conditional random field models, are popular in computer vision. However, in order to be computationally tractable, they are limited to ...
Sebastian Nowozin, Christoph H. Lampert
99
Voted
PRL
2006
225views more  PRL 2006»
14 years 10 months ago
A straight line detection using principal component analysis
A straight line detection algorithm is presented. The algorithm separates row and column edges from edge image using their primitive shapes. The edges are labeled, and the princip...
Yun-Seok Lee, Han-Suh Koo, Chang-Sung Jeong
ICML
2003
IEEE
15 years 11 months ago
Semi-Supervised Learning Using Gaussian Fields and Harmonic Functions
An approach to semi-supervised learning is proposed that is based on a Gaussian random field model. Labeled and unlabeled data are represented as vertices in a weighted graph, wit...
Xiaojin Zhu, Zoubin Ghahramani, John D. Lafferty
103
Voted
TIP
2008
181views more  TIP 2008»
14 years 10 months ago
Sparse Representation for Color Image Restoration
Abstract--Sparse representations of signals have drawn considerable interest in recent years. The assumption that natural signals, such as images, admit a sparse decomposition over...
Julien Mairal, Michael Elad, Guillermo Sapiro
PR
2002
121views more  PR 2002»
14 years 9 months ago
Statistical correlation analysis in image retrieval
A statistical correlation model for image retrieval is proposed. This model captures the semantic relationships among images in a database from simple statistics of userprovided r...
Mingjing Li, Zheng Chen, HongJiang Zhang