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» Applying Support Vector Machines to Imbalanced Datasets
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ISBI
2009
IEEE
14 years 3 months ago
Probabilistic Branching Node Detection Using Hybrid Local Features
Probabilistic branching node inference is an important step for analyzing branching patterns involved in many anatomic structures. We propose combining machine learning techniques...
Haibin Ling, Michael Barnathan, Vasileios Megalooi...
IVC
2006
187views more  IVC 2006»
13 years 9 months ago
Dynamics of facial expression extracted automatically from video
We present a systematic comparison of machine learning methods applied to the problem of fully automatic recognition of facial expressions, including AdaBoost, support vector mach...
Gwen Littlewort, Marian Stewart Bartlett, Ian R. F...
SCHOLARPEDIA
2008
89views more  SCHOLARPEDIA 2008»
13 years 7 months ago
Support vector clustering
We present a novel method for clustering using the support vector machine approach. Data points are mapped to a high dimensional feature space, where support vectors are used to d...
Asa Ben-Hur
IROS
2006
IEEE
136views Robotics» more  IROS 2006»
14 years 3 months ago
Panoramic View-Based Navigation in Outdoor Environments Based on Support Vector Learning
— This paper describes a panoramic view-based navigation in outdoor environments. We have been developing a two-phase navigation method. In the training phase, the robot acquires...
Hideo Morita, Michael Hild, Jun Miura, Yoshiaki Sh...
CIRA
2007
IEEE
147views Robotics» more  CIRA 2007»
14 years 3 months ago
Local Online Support Vector Regression for Learning Control
—Support vector regression (SVR) is a class of machine learning technique that has been successfully applied to low-level learning control in robotics. Because of the large amoun...
Younggeun Choi, Shin-Young Cheong, Nicolas Schweig...