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BMCBI
2008
88views more  BMCBI 2008»
14 years 9 months ago
Use of machine learning algorithms to classify binary protein sequences as highly-designable or poorly-designable
Background: By using a standard Support Vector Machine (SVM) with a Sequential Minimal Optimization (SMO) method of training, Na
Myron Peto, Andrzej Kloczkowski, Vasant Honavar, R...
ICRA
2006
IEEE
99views Robotics» more  ICRA 2006»
15 years 3 months ago
Human Motion Recognition with a Convolution Kernel
Abstract— We address the problem of human motion recognition in this paper. The goal of human motion recognition is to recognize the type of motion recorded in a video clip, whic...
Dongwei Cao, Osama Masoud, Daniel Boley
ICIC
2005
Springer
15 years 3 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-...
ICCV
2007
IEEE
15 years 3 months ago
Support Kernel Machines for Object Recognition
Kernel classifiers based on Support Vector Machines (SVM) have recently achieved state-of-the art results on several popular datasets like Caltech or Pascal. This was possible by...
Ankita Kumar, Cristian Sminchisescu
ECCV
2010
Springer
14 years 10 months ago
Object of Interest Detection by Saliency Learning
In this paper, we present a method for object of interest detection. This method is statistical in nature and hinges in a model which combines salient features using a mixture of l...