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» Learning the Compositional Nature of Visual Objects
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CVPR
2007
IEEE
14 years 8 months ago
Beyond bottom-up: Incorporating task-dependent influences into a computational model of spatial attention
A critical function in both machine vision and biological vision systems is attentional selection of scene regions worthy of further analysis by higher-level processes such as obj...
Robert J. Peters, Laurent Itti
VLSISP
2010
254views more  VLSISP 2010»
13 years 4 months ago
Manifold Based Local Classifiers: Linear and Nonlinear Approaches
Abstract In case of insufficient data samples in highdimensional classification problems, sparse scatters of samples tend to have many ‘holes’—regions that have few or no nea...
Hakan Cevikalp, Diane Larlus, Marian Neamtu, Bill ...
SIAMIS
2010
378views more  SIAMIS 2010»
13 years 21 days ago
Global Interactions in Random Field Models: A Potential Function Ensuring Connectedness
Markov random field (MRF) models, including conditional random field models, are popular in computer vision. However, in order to be computationally tractable, they are limited to ...
Sebastian Nowozin, Christoph H. Lampert