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» Feature Selection for Density Level-Sets
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CVPR
1999
IEEE
1104views Computer Vision» more  CVPR 1999»
14 years 10 months ago
Geodesic Active Contours for Supervised Texture Segmentation
This paper presents a variational method for supervised texture segmentation, which is based on ideas coming from the curve propagation theory. We assume that a preferable texture...
Nikos Paragios, Rachid Deriche
SECON
2008
IEEE
14 years 2 months ago
A Multi-AP Architecture for High-Density WLANs: Protocol Design and Experimental Evaluation
—Fast proliferation of IEEE 802.11 wireless devices has led to the emergence of High-Density (HD) Wireless Local Area Networks (WLANs), where it is challenging to improve the thr...
Yanfeng Zhu, Zhisheng Niu, Qian Zhang, Bo Tan, Zhi...
NIPS
2004
13 years 10 months ago
The Laplacian PDF Distance: A Cost Function for Clustering in a Kernel Feature Space
A new distance measure between probability density functions (pdfs) is introduced, which we refer to as the Laplacian pdf distance. The Laplacian pdf distance exhibits a remarkabl...
Robert Jenssen, Deniz Erdogmus, José Carlos...
CVPR
2012
IEEE
11 years 11 months ago
Background modeling using adaptive pixelwise kernel variances in a hybrid feature space
Recent work on background subtraction has shown developments on two major fronts. In one, there has been increasing sophistication of probabilistic models, from mixtures of Gaussi...
Manjunath Narayana, Allen R. Hanson, Erik G. Learn...
NN
2010
Springer
183views Neural Networks» more  NN 2010»
13 years 7 months ago
Dimensionality reduction for density ratio estimation in high-dimensional spaces
The ratio of two probability density functions is becoming a quantity of interest these days in the machine learning and data mining communities since it can be used for various d...
Masashi Sugiyama, Motoaki Kawanabe, Pui Ling Chui