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TSP
2010
13 years 2 months ago
Distributed sparse linear regression
The Lasso is a popular technique for joint estimation and continuous variable selection, especially well-suited for sparse and possibly under-determined linear regression problems....
Gonzalo Mateos, Juan Andrés Bazerque, Georg...
ICCV
2005
IEEE
14 years 1 months ago
Fast Global Kernel Density Mode Seeking with Application to Localisation and Tracking
We address the problem of seeking the global mode of a density function using the mean shift algorithm. Mean shift, like other gradient ascent optimisation methods, is susceptible...
Chunhua Shen, Michael J. Brooks, Anton van den Hen...
ECCV
2004
Springer
14 years 9 months ago
Learning to Segment
Abstract. We describe a new approach for learning to perform classbased segmentation using only unsegmented training examples. As in previous methods, we first use training images ...
Eran Borenstein, Shimon Ullman

Publication
173views
12 years 6 months ago
Max-Flow Segmentation of the Left Ventricle by Recovering Subject-Specific Distributions via a Bound of the Bhattacharyya Measur
This study investigates fast detection of the left ventricle (LV) endo- and epicardium boundaries in a cardiac magnetic resonance (MR) sequence following the optimization of two or...
Ismail Ben Ayed, Hua-mei Chen, Kumaradevan Punitha...
IPSN
2007
Springer
14 years 1 months ago
Robust system multiangulation using subspace methods
Sensor location information is a prerequisite to the utility of most sensor networks. In this paper we present a robust and low-complexity algorithm to self-localize and orient se...
Joshua N. Ash, Lee C. Potter