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TMM
2002
104views more  TMM 2002»
15 years 6 months ago
Spatial contextual classification and prediction models for mining geospatial data
Modeling spatial context (e.g., autocorrelation) is a key challenge in classification problems that arise in geospatial domains. Markov random fields (MRF) is a popular model for i...
Shashi Shekhar, Paul R. Schrater, Ranga Raju Vatsa...
PAMI
2007
187views more  PAMI 2007»
15 years 6 months ago
Supervised Learning of Semantic Classes for Image Annotation and Retrieval
—A probabilistic formulation for semantic image annotation and retrieval is proposed. Annotation and retrieval are posed as classification problems where each class is defined as...
Gustavo Carneiro, Antoni B. Chan, Pedro J. Moreno,...
ICMI
2009
Springer
175views Biometrics» more  ICMI 2009»
15 years 4 months ago
Discovering group nonverbal conversational patterns with topics
This paper addresses the problem of discovering conversational group dynamics from nonverbal cues extracted from thin-slices of interaction. We first propose and analyze a novel t...
Dinesh Babu Jayagopi, Daniel Gatica-Perez
JMLR
2010
192views more  JMLR 2010»
15 years 1 months ago
Inducing Tree-Substitution Grammars
Inducing a grammar from text has proven to be a notoriously challenging learning task despite decades of research. The primary reason for its difficulty is that in order to induce...
Trevor Cohn, Phil Blunsom, Sharon Goldwater
CVPR
2011
IEEE
14 years 10 months ago
Connecting Non-Quadratic Variational Models and MRFs
Spatially-discrete Markov random fields (MRFs) and spatially-continuous variational approaches are ubiquitous in low-level vision, including image restoration, segmentation, opti...
Kevin Schelten, Stefan Roth