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ECCV
2008
Springer
16 years 8 months ago
Weakly Supervised Object Localization with Stable Segmentations
Multiple Instance Learning (MIL) provides a framework for training a discriminative classifier from data with ambiguous labels. This framework is well suited for the task of learni...
Carolina Galleguillos, Boris Babenko, Andrew Rabin...
ICPR
2006
IEEE
16 years 7 months ago
Multiple Object Tracking Using Local PCA
Tracking multiple interacting objects represents a challenging area in computer vision. The tracking problem in general can be formulated as the task of recovering the spatio-temp...
Bernhard Frühstück, Csaba Beleznai, Hors...
UAI
1997
15 years 7 months ago
A Bayesian Approach to Learning Bayesian Networks with Local Structure
Recently several researchers have investigated techniques for using data to learn Bayesian networks containing compact representations for the conditional probability distribution...
David Maxwell Chickering, David Heckerman, Christo...
CSDA
2006
103views more  CSDA 2006»
15 years 6 months ago
LASS: a tool for the local analysis of self-similarity
The Hurst parameter H characterizes the degree of long-range dependence (and asymptotic selfsimilarity) in stationary time series. Many methods have been developed for the estimat...
Stilian Stoev, Murad S. Taqqu, Cheolwoo Park, Geor...
IJCV
1998
105views more  IJCV 1998»
15 years 5 months ago
Robust Algorithms for Object Localization
Object localization using sensed data features and corresponding model features is a fundamental problem in machine vision. We reformulate object localization as a least squares p...
Aaron S. Wallack, Dinesh Manocha