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TMI
2010
172views more  TMI 2010»
13 years 6 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...
ICPR
2008
IEEE
14 years 9 months ago
A machine learning based scheme for double JPEG compression detection
Double JPEG compression detection is of significance in digital forensics. We propose an effective machine learning based scheme to distinguish between double and single JPEG comp...
Chunhua Chen, Wei Su, Yun Q. Shi
IJCNN
2000
IEEE
13 years 11 months ago
Pose Classification Using Support Vector Machines
The field of human-computer interaction has been widely investigated in the last years, resulting in a variety of systems used in different application fields like virtual reality...
Edoardo Ardizzone, Antonio Chella, Roberto Pirrone
ICARCV
2002
IEEE
109views Robotics» more  ICARCV 2002»
14 years 26 days 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
ICML
2004
IEEE
14 years 8 months ago
Co-EM support vector learning
Multi-view algorithms, such as co-training and co-EM, utilize unlabeled data when the available attributes can be split into independent and compatible subsets. Co-EM outperforms ...
Ulf Brefeld, Tobias Scheffer