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TMI
2010
172views more  TMI 2010»
13 years 4 months ago
Comparison of AdaBoost and Support Vector Machines for Detecting Alzheimer's Disease Through Automated Hippocampal Segmentation
Abstract— We compared four automated methods for hippocampal segmentation using different machine learning algorithms (1) hierarchical AdaBoost, (2) Support Vector Machines (SVM)...
Jonathan H. Morra, Zhuowen Tu, Liana G. Apostolova...
NIPS
2004
13 years 7 months ago
A Topographic Support Vector Machine: Classification Using Local Label Configurations
The standard approach to the classification of objects is to consider the examples as independent and identically distributed (iid). In many real world settings, however, this ass...
Johannes Mohr, Klaus Obermayer
ICIC
2005
Springer
13 years 11 months ago
Methods of Decreasing the Number of Support Vectors via k-Mean Clustering
This paper proposes two methods which take advantage of k -mean clustering algorithm to decrease the number of support vectors (SVs) for the training of support vector machine (SVM...
Xiao-Lei Xia, Michael R. Lyu, Tat-Ming Lok, Guang-...
ACIVS
2009
Springer
13 years 10 months ago
Vehicle Tracking Using Geometric Features
Applications such as traffic surveillance require a real-time and accurate method for object tracking. We propose to represent scene observations with parabola segments with an alg...
Francis Deboeverie, Kristof Teelen, Peter Veelaert...
ICPR
2002
IEEE
14 years 7 months ago
Incorporating Conditional Independence Assumption with Support Vector Machines to Enhance Handwritten Character Segmentation Per
Learning Bayesian Belief Networks (BBN) from corpora and incorporating the extracted inferring knowledge with a Support Vector Machines (SVM) classifier has been applied to charac...
Manolis Maragoudakis, Ergina Kavallieratou, Nikos ...