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» Random walks on graphs to model saliency in images
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ICDM
2005
IEEE
190views Data Mining» more  ICDM 2005»
15 years 6 months ago
Neighborhood Formation and Anomaly Detection in Bipartite Graphs
Many real applications can be modeled using bipartite graphs, such as users vs. files in a P2P system, traders vs. stocks in a financial trading system, conferences vs. authors ...
Jimeng Sun, Huiming Qu, Deepayan Chakrabarti, Chri...
110
Voted
ECML
2004
Springer
15 years 5 months ago
The Principal Components Analysis of a Graph, and Its Relationships to Spectral Clustering
This work presents a novel procedure for computing (1) distances between nodes of a weighted, undirected, graph, called the Euclidean Commute Time Distance (ECTD), and (2) a subspa...
Marco Saerens, François Fouss, Luh Yen, Pie...
CVPR
2010
IEEE
15 years 5 months ago
Facial Point Detection using Boosted Regression and Graph Models
Finding fiducial facial points in any frame of a video showing rich naturalistic facial behaviour is an unsolved problem. Yet this is a crucial step for geometric-featurebased fa...
Michel Valstar, Brais Martinez, Xavier Binefa, Maj...
DAGM
2008
Springer
15 years 2 months ago
MAP-Inference for Highly-Connected Graphs with DC-Programming
The design of inference algorithms for discrete-valued Markov Random Fields constitutes an ongoing research topic in computer vision. Large state-spaces, none-submodular energy-fun...
Jörg H. Kappes, Christoph Schnörr
MICCAI
2010
Springer
14 years 10 months ago
Non-parametric Iterative Model Constraint Graph min-cut for Automatic Kidney Segmentation
We present a new non-parametric model constraint graph min-cut algorithm for automatic kidney segmentation in CT images. The segmentation is formulated as a maximum a-posteriori es...
Moti Freiman, A. Kronman, S. J. Esses, Leo Joskowi...