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ML
1998
ACM
153views Machine Learning» more  ML 1998»
13 years 7 months ago
Bayesian Landmark Learning for Mobile Robot Localization
To operate successfully in indoor environments, mobile robots must be able to localize themselves. Most current localization algorithms lack flexibility, autonomy, and often optim...
Sebastian Thrun
CVPR
2003
IEEE
14 years 9 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
CVPR
2000
IEEE
14 years 9 months ago
Towards Automatic Discovery of Object Categories
We propose a method to learn heterogeneous models of object classes for visual recognition. The training images contain a preponderance of clutter and learning is unsupervised. Ou...
Markus Weber, Max Welling, Pietro Perona
CVPR
2009
IEEE
13 years 11 months ago
Learning to associate: HybridBoosted multi-target tracker for crowded scene
We propose a learning-based hierarchical approach of multi-target tracking from a single camera by progressively associating detection responses into longer and longer track fragm...
Yuan Li, Chang Huang, Ram Nevatia
ICML
2008
IEEE
14 years 8 months ago
Expectation-maximization for sparse and non-negative PCA
We study the problem of finding the dominant eigenvector of the sample covariance matrix, under additional constraints on the vector: a cardinality constraint limits the number of...
Christian D. Sigg, Joachim M. Buhmann