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CVPR
2008
IEEE
16 years 8 months ago
A hierarchical and contextual model for aerial image understanding
In this paper we present a novel method for parsing aerial images with a hierarchical and contextual model learned in a statistical framework. We learn hierarchies at the scene an...
Jake Porway, Kristy Wang, Benjamin Yao, Song Chun ...
CVPR
2007
IEEE
16 years 8 months ago
Modelling Objects using Distribution and Topology of Multiscale Region Pairs
We propose a method for simultaneous detection, localization and segmentation of objects of a known category. We show that this is possible by using segments as features. To this ...
Himanshu Arora, Narendra Ahuja
JMLR
2012
13 years 9 months ago
Low rank continuous-space graphical models
Constructing tractable dependent probability distributions over structured continuous random vectors is a central problem in statistics and machine learning. It has proven diffic...
Carl Smith, Frank Wood, Liam Paninski
LATA
2010
Springer
16 years 1 months ago
Extending Stochastic Context-Free Grammars for an Application in Bioinformatics
We extend stochastic context-free grammars such that the probability of applying a production can depend on the length of the subword that is generated from the application and sho...
Frank Weinberg, Markus E. Nebel
CORR
2010
Springer
96views Education» more  CORR 2010»
15 years 6 months ago
Learning High-Dimensional Markov Forest Distributions: Analysis of Error Rates
The problem of learning forest-structured discrete graphical models from i.i.d. samples is considered. An algorithm based on pruning of the Chow-Liu tree through adaptive threshol...
Vincent Y. F. Tan, Animashree Anandkumar, Alan S. ...