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» A Markov Random Field Model of Microarray Gridding
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JCB
2006
215views more  JCB 2006»
14 years 9 months ago
Protein Fold Recognition Using Segmentation Conditional Random Fields (SCRFs)
Protein fold recognition is an important step towards understanding protein three-dimensional structures and their functions. A conditional graphical model, i.e., segmentation con...
Yan Liu 0002, Jaime G. Carbonell, Peter Weigele, V...
73
Voted
ICPR
2004
IEEE
15 years 10 months ago
Photometric Stereo Under Blurred Observations
In this paper we address the problem of simultaneous estimation of structure and restoration of images from blurred photometric measurements. Given the blurred observations of a s...
Manjunath V. Joshi, Subhasis Chaudhuri
INTERSPEECH
2010
14 years 4 months ago
Deep-structured hidden conditional random fields for phonetic recognition
We extend our earlier work on deep-structured conditional random field (DCRF) and develop deep-structured hidden conditional random field (DHCRF). We investigate the use of this n...
Dong Yu, Li Deng
102
Voted
VMV
2008
165views Visualization» more  VMV 2008»
14 years 11 months ago
Fast Global Labeling for Real-Time Stereo Using Multiple Plane Sweeps
This work presents a real-time, data-parallel approach for global label assignment on regular grids. The labels are selected according to a Markov random field energy with a Potts...
Christopher Zach, David Gallup, Jan-Michael Frahm,...
ECCV
2010
Springer
14 years 11 months ago
Image Segmentation with Topic Random Field
Abstract. Recently, there has been increasing interests in applying aspect models (e.g., PLSA and LDA) in image segmentation. However, these models ignore spatial relationships amo...