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150
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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
160
Voted
MTA
2007
110views more  MTA 2007»
15 years 4 months ago
On aggregate available bandwidth in many-to-one data transfer - modeling and applications
Abstract This work investigates the modeling of aggregate available bandwidth in multisender network applications. Unlike the well-established client–server model, where there is...
S. C. Hui, Jack Y. B. Lee
MA
2010
Springer
132views Communications» more  MA 2010»
15 years 3 months ago
Model selection by sequentially normalized least squares
Model selection by the predictive least squares (PLS) principle has been thoroughly studied in the context of regression model selection and autoregressive (AR) model order estima...
Jorma Rissanen, Teemu Roos, Petri Myllymäki
CVPR
2007
IEEE
16 years 6 months ago
Unsupervised Activity Perception by Hierarchical Bayesian Models
We propose a novel unsupervised learning framework for activity perception. To understand activities in complicated scenes from visual data, we propose a hierarchical Bayesian mod...
Xiaogang Wang, Xiaoxu Ma, Eric Grimson
ECCV
2000
Springer
16 years 6 months ago
Non-linear Bayesian Image Modelling
In recent years several techniques have been proposed for modelling the low-dimensional manifolds, or `subspaces', of natural images. Examples include principal component anal...
Christopher M. Bishop, John M. Winn