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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
ICMCS
2005
IEEE
82views Multimedia» more  ICMCS 2005»
14 years 1 months ago
An Extended Motion-Estimation Architecture Applied to Shape Recognition
An architecture for shape recognition is presented, with emphasis on low-latency and power efficiency. This architecture is an extension of an existing architecture used for moti...
Jason Schlessman, Sankalita Saha, Wayne Wolf, Shuv...
SPEECH
1998
77views more  SPEECH 1998»
13 years 7 months ago
Impairment of speech-reading in prosopagnosia
The face is a source of information processed by a complex system of partly independent subsystems. The extent of the independence of processing personal identity, facial expressi...
Béatrice de Gelder, Jean Vroomen
CEC
2010
IEEE
13 years 9 months ago
An adaptive ensemble of fuzzy ARTMAP neural networks for video-based face classification
A key feature in population based optimization algorithms is the ability to explore a search space and make a decision based on multiple solutions. In this paper, an incremental le...
Jean-François Connolly, Eric Granger, Rober...
IJCV
2007
196views more  IJCV 2007»
13 years 7 months ago
Weakly Supervised Scale-Invariant Learning of Models for Visual Recognition
We investigate a method for learning object categories in a weakly supervised manner. Given a set of images known to contain the target category from a similar viewpoint, learning...
Robert Fergus, Pietro Perona, Andrew Zisserman