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NIPS
2001
15 years 5 months ago
Unsupervised Learning of Human Motion Models
This paper presents an unsupervised learning algorithm that can derive the probabilistic dependence structure of parts of an object (a moving human body in our examples) automatic...
Yang Song, Luis Goncalves, Pietro Perona
AIR
2006
107views more  AIR 2006»
15 years 4 months ago
Just enough learning (of association rules): the TAR2 "Treatment" learner
Abstract. An over-zealous machine learner can automatically generate large, intricate, theories which can be hard to understand. However, such intricate learning is not necessary i...
Tim Menzies, Ying Hu
IJCV
2007
196views more  IJCV 2007»
15 years 4 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
ICIP
2009
IEEE
15 years 2 months ago
Object tracking by bidirectional learning with feature selection
This paper proposes a new tracking algorithm which combines object and background information, via building object and background appearance models simultaneously by nonparametric...
Heng Wang, Xinwen Hou, Cheng-Lin Liu
ICST
2009
IEEE
15 years 2 months ago
Test Redundancy Measurement Based on Coverage Information: Evaluations and Lessons Learned
Measurement and detection of redundancy in test suites attempt to achieve test minimization which in turn can help reduce test maintenance costs, and to also ensure the integrity ...
Negar Koochakzadeh, Vahid Garousi, Frank Maurer