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» Causal inference using the algorithmic Markov condition
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ACCV
2010
Springer
13 years 5 months ago
MRF-Based Background Initialisation for Improved Foreground Detection in Cluttered Surveillance Videos
Abstract. Robust foreground object segmentation via background modelling is a difficult problem in cluttered environments, where obtaining a clear view of the background to model i...
Vikas Reddy, Conrad Sanderson, Andres Sanin, Brian...
KDD
2008
ACM
259views Data Mining» more  KDD 2008»
14 years 10 months ago
Using ghost edges for classification in sparsely labeled networks
We address the problem of classification in partially labeled networks (a.k.a. within-network classification) where observed class labels are sparse. Techniques for statistical re...
Brian Gallagher, Hanghang Tong, Tina Eliassi-Rad, ...
ICDCS
2007
IEEE
14 years 4 months ago
Uniform Data Sampling from a Peer-to-Peer Network
Uniform random sample is often useful in analyzing data. Usually taking a uniform sample is not a problem if the entire data resides in one location. However, if the data is distr...
Souptik Datta, Hillol Kargupta
PAMI
2010
417views more  PAMI 2010»
13 years 8 months ago
Auto-Context and Its Application to High-Level Vision Tasks and 3D Brain Image Segmentation
The notion of using context information for solving high-level vision and medical image segmentation problems has been increasingly realized in the field. However, how to learn a...
Zhuowen Tu, Xiang Bai
ECP
1997
Springer
92views Robotics» more  ECP 1997»
14 years 2 months ago
Understanding and Extending Graphplan
We provide a reconstruction of Blum and Furst’s Graphplan algorithm, and use the reconstruction to extend and improve the original algorithm in several ways. In our reconstructi...
Subbarao Kambhampati, Eric Parker, Eric Lambrecht