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TMI
2010
172views more  TMI 2010»
14 years 10 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...
ESWA
2006
122views more  ESWA 2006»
14 years 12 months ago
Transmembrane segments prediction and understanding using support vector machine and decision tree
In recent years, there have been many studies focusing on improving the accuracy of prediction of transmembrane segments, and many significant results have been achieved. In spite...
Jieyue He, Hae-Jin Hu, Robert W. Harrison, Phang C...
ICANN
2009
Springer
15 years 4 months ago
Learning SVMs from Sloppily Labeled Data
This paper proposes a modelling of Support Vector Machine (SVM) learning to address the problem of learning with sloppy labels. In binary classification, learning with sloppy labe...
Guillaume Stempfel, Liva Ralaivola
ICARCV
2002
IEEE
109views Robotics» more  ICARCV 2002»
15 years 4 months ago
Quantized wavelet features and support vector machines for on-road vehicle detection
The focus of this work is on the problem of feature selection and classification for on-road vehicle detection. In particular, we propose using quantized Haar wavelet features an...
Zehang Sun, George Bebis, Ronald Miller
BMCBI
2007
147views more  BMCBI 2007»
14 years 12 months ago
Improved residue contact prediction using support vector machines and a large feature set
Background: Predicting protein residue-residue contacts is an important 2D prediction task. It is useful for ab initio structure prediction and understanding protein folding. In s...
Jianlin Cheng, Pierre Baldi