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ICASSP
2010
IEEE
13 years 9 months ago
Utilizing principal singular vectors for two-dimensional single frequency estimation
In this paper, frequency estimation of a twodimensional (2D) cisoid in the presence of additive white Gaussian noise is addressed. By utilizing the rank-one property of the 2D noi...
H. C. So, Frankie K. W. Chan, C. F. Chan, W. H. La...
JMLR
2008
114views more  JMLR 2008»
13 years 9 months ago
Coordinate Descent Method for Large-scale L2-loss Linear Support Vector Machines
Linear support vector machines (SVM) are useful for classifying large-scale sparse data. Problems with sparse features are common in applications such as document classification a...
Kai-Wei Chang, Cho-Jui Hsieh, Chih-Jen Lin
TVCG
2012
213views Hardware» more  TVCG 2012»
11 years 11 months ago
Mesh-Driven Vector Field Clustering and Visualization: An Image-Based Approach
—Vector field visualization techniques have evolved very rapidly over the last two decades, however, visualizing vector fields on complex boundary surfaces from computational ...
Zhenmin Peng, Edward Grundy, Robert S. Laramee, Gu...
ICIP
2006
IEEE
14 years 10 months ago
Support Vector Machines for Camera Calibration Problem
This paper presents a statistical learning-based solution to the camera calibration problem in which the Support Vector Machines (SVM) are used for the estimation of the projectio...
Refaat M. Mohamed, Abdelrehim H. Ahmed, Ahmed Eid,...
ICIP
2005
IEEE
14 years 10 months ago
Learning hidden semantic cues using support vector clustering
This paper presents a method to infer hidden semantic cues by accumulating the knowledge learned from relevance feedback sessions. We propose to explicitly represent a semantic sp...
Jia-Wen Tung, Chiou-Ting Hsu