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» Gender Classification Using Support Vector Machines
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TNN
2010
205views Management» more  TNN 2010»
14 years 9 months ago
Behavior-constrained support vector machines for fMRI data analysis
Statistical learning methods are emerging as a valuable tool for decoding information from neural imaging data. The noisy signal and the limited number of training patterns that ar...
Danmei Chen, Sheng Li, Zoe Kourtzi, Si Wu
TMI
2010
172views more  TMI 2010»
15 years 24 days 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...
ICANN
2001
Springer
15 years 7 months ago
Fast Training of Support Vector Machines by Extracting Boundary Data
Support vector machines have gotten wide acceptance for their high generalization ability for real world applications. But the major drawback is slow training for classification p...
Shigeo Abe, Takuya Inoue
ICARCV
2002
IEEE
109views Robotics» more  ICARCV 2002»
15 years 7 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
PR
2010
163views more  PR 2010»
15 years 26 days ago
Optimal feature selection for support vector machines
Selecting relevant features for Support Vector Machine (SVM) classifiers is important for a variety of reasons such as generalization performance, computational efficiency, and ...
Minh Hoai Nguyen, Fernando De la Torre