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» Modeling Image Textures by Gibbs Random Fields
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92
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IJCV
2008
266views more  IJCV 2008»
15 years 17 days ago
Learning to Recognize Objects with Little Supervision
This paper shows (i) improvements over state-of-the-art local feature recognition systems, (ii) how to formulate principled models for automatic local feature selection in object c...
Peter Carbonetto, Gyuri Dorkó, Cordelia Sch...
114
Voted
ICCV
2007
IEEE
16 years 2 months ago
On the Differential Geometry of 3D Flow Patterns: Generalized Helicoids and Diffusion MRI Analysis
Configurations of dense locally parallel 3D curves occur in medical imaging, computer vision and graphics. Examples include white matter fibre tracts, textures, fur and hair. We d...
Peter Savadjiev, Steven W. Zucker, Kaleem Siddiqi
NIPS
2008
15 years 2 months ago
Natural Image Denoising with Convolutional Networks
We present an approach to low-level vision that combines two main ideas: the use of convolutional networks as an image processing architecture and an unsupervised learning procedu...
Viren Jain, H. Sebastian Seung
TMI
2010
133views more  TMI 2010»
14 years 11 months ago
Synthetic Magnetic Resonance Imaging Revisited
—Synthetic magnetic resonance (MR) imaging is an approach suggested in the literature to predict MR images at different design parameter settings from at least three observed MR ...
Ranjan Maitra, John J. Riddles
ICIP
2008
IEEE
16 years 2 months ago
Implicit spatial inference with sparse local features
This paper introduces a novel way to leverage the implicit geometry of sparse local features (e.g. SIFT operator) for the purposes of object detection and segmentation. A two-clas...
Deirdre O'Regan, Anil C. Kokaram