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» Markov Random Field Models in Computer Vision
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KDD
2004
ACM
132views Data Mining» more  KDD 2004»
16 years 2 months ago
A probabilistic framework for semi-supervised clustering
Unsupervised clustering can be significantly improved using supervision in the form of pairwise constraints, i.e., pairs of instances labeled as belonging to same or different clu...
Sugato Basu, Mikhail Bilenko, Raymond J. Mooney
PAMI
2002
108views more  PAMI 2002»
15 years 1 months ago
Approximate Bayes Factors for Image Segmentation: The Pseudolikelihood Information Criterion (PLIC)
We propose a method for choosing the number of colors or true gray levels in an image; this allows fully automatic segmentation of images. Our underlying probability model is a hid...
Derek C. Stanford, Adrian E. Raftery
ICDE
2011
IEEE
207views Database» more  ICDE 2011»
14 years 5 months ago
Monte Carlo query processing of uncertain multidimensional array data
— Array database systems are architected for scientific and engineering applications. In these applications, the value of a cell is often imprecise and uncertain. There are at le...
Tingjian Ge, David Grabiner, Stanley B. Zdonik
ICPR
2010
IEEE
15 years 8 months ago
Probabilistic Modeling of Dynamic Traffic Flow across Non-Overlapping Camera Views
In this paper, we propose a probabilistic method to model the dynamic traffic flow across nonoverlapping camera views. By assuming the transition time of object movement follows a...
Ching-Chun Huang, Wei-Chen Chiu, Sheng-Jyh Wang, J...
ICPR
2008
IEEE
15 years 8 months ago
Fingerprint orientation analysis with topological modeling
This paper proposes to characterize the fingerprint orientation using a novel topological representation, which transforms the orientation field into a map composed of a set of ...
Zujun Hou, Jun Li, Hwee Keong Lam, Tai Pang Chen, ...