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CVPR
2011
IEEE
13 years 5 months ago
Learning invariance through imitation
Supervised methods for learning an embedding aim to map high-dimensional images to a space in which perceptually similar observations have high measurable similarity. Most approac...
Graham Taylor, Ian Spiro, Rob Fergus, Christoph Br...
FOCM
2011
113views more  FOCM 2011»
13 years 4 months ago
Finite Resolution Dynamics
We develop a new mathematical model for describing a dynamical system at limited resolution (or finite scale), and we give precise meaning to the notion of a dynamical system havi...
Stefano Luzzatto, Pawel Pilarczyk
VLDB
2003
ACM
165views Database» more  VLDB 2003»
14 years 9 months ago
Learning to match ontologies on the Semantic Web
On the Semantic Web, data will inevitably come from many different ontologies, and information processing across ontologies is not possible without knowing the semantic mappings be...
AnHai Doan, Jayant Madhavan, Robin Dhamankar, Pedr...
DGCI
2003
Springer
14 years 2 months ago
Shape Similarity and Visual Parts
Abstract. Human perception of shape is based on visual parts of objects to a point that a single, significant visual part is sufficient to recognize the whole object. For example,...
Longin Jan Latecki, Rolf Lakämper, Diedrich W...
ICCV
1998
IEEE
14 years 11 months ago
View-Based Object Matching
W e introduce a novel view-based object representation, called the saliency map graph (SMG), which captures the salient regions of an object view at multiple scales using a wavele...
Ali Shokoufandeh, Ivan Marsic, Sven J. Dickinson