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CVPR
2003
IEEE
14 years 10 months ago
Object Class Recognition by Unsupervised Scale-Invariant Learning
We present a method to learn and recognize object class models from unlabeled and unsegmented cluttered scenes in a scale invariant manner. Objects are modeled as flexible constel...
Robert Fergus, Pietro Perona, Andrew Zisserman
ECCV
1998
Springer
14 years 9 months ago
A Two-Stage Probabilistic Approach for Object Recognition
Assume that some objects are present in an image but can be seen only partially and are overlapping each other. To recognize the objects, we have to rstly separate the objects from...
Stan Z. Li, Joachim Hornegger
PAMI
2012
11 years 10 months ago
Unsupervised Learning of Categorical Segments in Image Collections
Which one comes first: segmentation or recognition? We propose a unified framework for carrying out the two simultaneously and without supervision. The framework combines a fle...
Marco Andreetto, Lihi Zelnik-Manor, Pietro Perona
GRAPHICSINTERFACE
2008
13 years 9 months ago
SurfaceFusion: unobtrusive tracking of everyday objects in tangible user interfaces
Interactive surfaces and related tangible user interfaces often involve everyday objects that are identified, tracked, and augmented with digital information. Traditional approach...
Alex Olwal, Andrew D. Wilson
GECCO
2006
Springer
171views Optimization» more  GECCO 2006»
13 years 11 months ago
Evolving ensemble of classifiers in random subspace
Various methods for ensemble selection and classifier combination have been designed to optimize the results of ensembles of classifiers. Genetic algorithm (GA) which uses the div...
Albert Hung-Ren Ko, Robert Sabourin, Alceu de Souz...