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TFS
2008
174views more  TFS 2008»
13 years 7 months ago
Type-2 Fuzzy Markov Random Fields and Their Application to Handwritten Chinese Character Recognition
In this paper, we integrate type-2 (T2) fuzzy sets with Markov random fields (MRFs) referred to as T2 FMRFs, which may handle both fuzziness and randomness in the structural patter...
Jia Zeng, Zhi-Qiang Liu
NIPS
2008
13 years 9 months ago
Multiscale Random Fields with Application to Contour Grouping
We introduce a new interpretation of multiscale random fields (MSRFs) that admits efficient optimization in the framework of regular (single level) random fields (RFs). It is base...
Longin Jan Latecki, ChengEn Lu, Marc Sobel, Xiang ...
WSCG
2004
217views more  WSCG 2004»
13 years 9 months ago
Blending Textured Images Using a Non-parametric Multiscale MRF Method
In this paper we describe a new method for improving the representation of textures in blends of multiple images based on a Markov Random Field (MRF) algorithm. We show that direc...
Bernard Tiddeman
MIA
2010
170views more  MIA 2010»
13 years 2 months ago
Linear intensity-based image registration by Markov random fields and discrete optimization
We propose a framework for intensity-based registration of images by linear transformations, based on a discrete Markov Random Field (MRF) formulation. Here, the challenge arises ...
Darko Zikic, Ben Glocker, Oliver Kutter, Martin Gr...
PAMI
2010
417views more  PAMI 2010»
13 years 6 months ago
Auto-Context and Its Application to High-Level Vision Tasks and 3D Brain Image Segmentation
The notion of using context information for solving high-level vision and medical image segmentation problems has been increasingly realized in the field. However, how to learn a...
Zhuowen Tu, Xiang Bai