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» A Training Method with Small Computation for Classification
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MOC
1998
102views more  MOC 1998»
13 years 7 months ago
Classification of integral lattices with large class number
A detailed exposition of Kneser’s neighbour method for quadratic lattices over totally real number fields, and of the sub-procedures needed for its implementation, is given. Usi...
Rudolf Scharlau, Boris Hemkemeier
BMCBI
2008
106views more  BMCBI 2008»
13 years 8 months ago
A machine vision system for automated non-invasive assessment of cell viability via dark field microscopy, wavelet feature selec
Background: Cell viability is one of the basic properties indicating the physiological state of the cell, thus, it has long been one of the major considerations in biotechnologica...
Ning Wei, Erwin Flaschel, Karl Friehs, Tim W. Natt...
ICASSP
2011
IEEE
12 years 11 months ago
Sparse common spatial patterns in brain computer interface applications
The Common Spatial Pattern (CSP) method is a powerful technique for feature extraction from multichannel neural activity and widely used in brain computer interface (BCI) applicat...
Fikri Goksu, Nuri Firat Ince, Ahmed H. Tewfik
JMLR
2010
115views more  JMLR 2010»
13 years 2 months ago
Fast and Scalable Local Kernel Machines
A computationally efficient approach to local learning with kernel methods is presented. The Fast Local Kernel Support Vector Machine (FaLK-SVM) trains a set of local SVMs on redu...
Nicola Segata, Enrico Blanzieri
ICCV
2003
IEEE
14 years 9 months ago
Object Recognition with Informative Features and Linear Classification
In this paper we show that efficient object recognition can be obtained by combining informative features with linear classification. The results demonstrate the superiority of in...
Michel Vidal-Naquet, Shimon Ullman