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IJCV
2008
151views more  IJCV 2008»
14 years 9 months ago
Describing Visual Scenes Using Transformed Objects and Parts
We develop hierarchical, probabilistic models for objects, the parts composing them, and the visual scenes surrounding them. Our approach couples topic models originally developed...
Erik B. Sudderth, Antonio Torralba, William T. Fre...
DFT
2005
IEEE
102views VLSI» more  DFT 2005»
14 years 11 months ago
Using Statistical Transformations to Improve Compression for Linear Decompressors
Linear decompressors are the dominant methodology used in commercial test data compression tools. However, they are generally not able to exploit correlations in the test data, an...
Samuel I. Ward, Chris Schattauer, Nur A. Touba
IJCAI
2003
14 years 10 months ago
A Learning Algorithm for Localizing People Based on Wireless Signal Strength that Uses Labeled and Unlabeled Data
This paper summarizes a probabilistic approach for localizing people through the signal strengths of a wireless IEEE 802.11b network. Our approach uses data labeled by ground trut...
Sebastian Thrun, Geoffrey J. Gordon, Frank Pfennin...
ICML
2007
IEEE
15 years 10 months ago
Linear and nonlinear generative probabilistic class models for shape contours
We introduce a robust probabilistic approach to modeling shape contours based on a lowdimensional, nonlinear latent variable model. In contrast to existing techniques that use obj...
Graham McNeill, Sethu Vijayakumar
ICCV
2003
IEEE
15 years 11 months ago
Automatically Labeling Video Data Using Multi-class Active Learning
Labeling video data is an essential prerequisite for many vision applications that depend on training data, such as visual information retrieval, object recognition, and human act...
Rong Yan, Jie Yang, Alexander G. Hauptmann