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» Structural Learning of Activities from Sparse Datasets
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CVPR
2011
IEEE
13 years 4 months ago
Novel 4-D Open-Curve Active Contour and Curve Completion Approach for Automated Tree Structure Extraction
We present novel approaches for fully automated extraction of tree-like tubular structures from 3-D image stacks. A 4-D Open-Curve Active Contour (Snake) model is proposed for sim...
Yu Wang, Arunachalam Narayanaswamy, Badri Roysam
KDD
2008
ACM
195views Data Mining» more  KDD 2008»
14 years 9 months ago
Anomaly pattern detection in categorical datasets
We propose a new method for detecting patterns of anomalies in categorical datasets. We assume that anomalies are generated by some underlying process which affects only a particu...
Kaustav Das, Jeff G. Schneider, Daniel B. Neill
ICPR
2008
IEEE
14 years 10 months ago
Beyond SVD: Sparse projections onto exemplar orthonormal bases for compact image representation
We present a new method for compact representation of large image datasets. Our method is based on treating small patches from an image as matrices as opposed to the conventional ...
Ajit Rajwade, Anand Rangarajan, Arunava Banerjee, ...
CVPR
2007
IEEE
14 years 10 months ago
Learning GMRF Structures for Spatial Priors
The goal of this paper is to find sparse and representative spatial priors that can be applied to part-based object localization. Assuming a GMRF prior over part configurations, w...
Lie Gu, Eric P. Xing, Takeo Kanade
ML
2006
ACM
142views Machine Learning» more  ML 2006»
13 years 8 months ago
The max-min hill-climbing Bayesian network structure learning algorithm
We present a new algorithm for Bayesian network structure learning, called Max-Min Hill-Climbing (MMHC). The algorithm combines ideas from local learning, constraint-based, and sea...
Ioannis Tsamardinos, Laura E. Brown, Constantin F....