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JCP
2008
171views more  JCP 2008»
13 years 7 months ago
Mining Frequent Subgraph by Incidence Matrix Normalization
Existing frequent subgraph mining algorithms can operate efficiently on graphs that are sparse, have vertices with low and bounded degrees, and contain welllabeled vertices and edg...
Jia Wu, Ling Chen
CGF
2010
168views more  CGF 2010»
13 years 8 months ago
Modeling Complex Unfoliaged Trees from a Sparse Set of Images
We present a novel image-based technique for modeling complex unfoliaged trees. Existing tree modeling tools either require capturing a large number of views for dense 3D reconstr...
Luis D. Lopez, Yuanyuan Ding, Jingyi Yu
ECCV
2008
Springer
14 years 9 months ago
Sparse Long-Range Random Field and Its Application to Image Denoising
Many recent techniques for low-level vision problems such as image denoising are formulated in terms of Markov random field (MRF) or conditional random field (CRF) models. Nonethel...
Yunpeng Li, Daniel P. Huttenlocher
ICASSP
2011
IEEE
12 years 11 months ago
Sampling on locally defined principal manifolds
We start with a locally defined principal curve definition for a given probability density function (pdf) and define a pairwise manifold score based on local derivatives of the...
Erhan Bas, Deniz Erdogmus
APVIS
2006
13 years 9 months ago
Increasing the readability of graph drawings with centrality-based scaling
A common problem in visualising some networks is the presence of localised high density areas in an otherwise sparse graph. Applying common graph drawing algorithms on such networ...
Damian Merrick, Joachim Gudmundsson