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SIAMIS
2010
156views more  SIAMIS 2010»
13 years 1 months ago
Learning the Morphological Diversity
This article proposes a new method for image separation into a linear combination of morphological components. Sparsity in fixed dictionaries is used to extract the cartoon and osc...
Gabriel Peyré, Jalal Fadili, Jean-Luc Starc...
ICCV
2011
IEEE
12 years 6 months ago
Perturb-and-MAP Random Fields: Using Discrete Optimization\\to Learn and Sample from Energy Models
We propose a novel way to induce a random field from an energy function on discrete labels. It amounts to locally injecting noise to the energy potentials, followed by finding t...
George Papandreou, Alan L. Yuille
ECCV
2008
Springer
14 years 8 months ago
Learning Optical Flow
Assumptions of brightness constancy and spatial smoothness underlie most optical flow estimation methods. In contrast to standard heuristic formulations, we learn a statistical mod...
Deqing Sun, Stefan Roth, J. P. Lewis, Michael J. B...
ICMI
2010
Springer
141views Biometrics» more  ICMI 2010»
13 years 4 months ago
Learning and evaluating response prediction models using parallel listener consensus
Traditionally listener response prediction models are learned from pre-recorded dyadic interactions. Because of individual differences in behavior, these recordings do not capture...
Iwan de Kok, Derya Ozkan, Dirk Heylen, Louis-Phili...
CONNECTION
2008
178views more  CONNECTION 2008»
13 years 6 months ago
Spoken language interaction with model uncertainty: an adaptive human-robot interaction system
Spoken language is one of the most intuitive forms of interaction between humans and agents. Unfortunately, agents that interact with people using natural language often experienc...
Finale Doshi, Nicholas Roy