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CSL
2006
Springer
13 years 7 months ago
Support vector machines for speaker and language recognition
Support vector machines (SVMs) have proven to be a powerful technique for pattern classification. SVMs map inputs into a high dimensional space and then separate classes with a hy...
William M. Campbell, Joseph P. Campbell, Douglas A...
BMCBI
2008
228views more  BMCBI 2008»
13 years 7 months ago
Adaptive diffusion kernel learning from biological networks for protein function prediction
Background: Machine-learning tools have gained considerable attention during the last few years for analyzing biological networks for protein function prediction. Kernel methods a...
Liang Sun, Shuiwang Ji, Jieping Ye
CVPR
2012
IEEE
11 years 9 months ago
SURFing the point clouds: Selective 3D spatial pyramids for category-level object recognition
This paper proposes a novel approach to recognize object categories in point clouds. By quantizing 3D SURF local descriptors, computed on partial 3D shapes extracted from the poin...
Carolina Redondo-Cabrera, Roberto Javier Ló...
ICIP
2001
IEEE
14 years 8 months ago
Higher order autocorrelations for pattern classification
The use of higher-order local autocorrelations as features for pattern recognition has been acknowledged since many years, but their applicability was restricted to relatively low...
Vlad Popovici, Jean-Philippe Thiran
NIPS
2003
13 years 8 months ago
Phonetic Speaker Recognition with Support Vector Machines
A recent area of significant progress in speaker recognition is the use of high level features—idiolect, phonetic relations, prosody, discourse structure, etc. A speaker not on...
William M. Campbell, Joseph P. Campbell, Douglas A...