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TMI
2010
172views more  TMI 2010»
15 years 15 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...
ICMLC
2010
Springer
15 years 20 days ago
An integrity-based fuzzy c-means method resolving cluster size sensitivity problem
: Cluster size insensitive FCM (csiFCM) dynamically adjusts the membership value of each object based on the size of the cluster to which it is assigned after defuzzification to re...
Y. H. Lai, P. W. Huang, P. L. Lin
88
Voted
EMNLP
2009
14 years 12 months ago
How well does active learning
Machine involvement has the potential to speed up language documentation. We assess this potential with timed annotation experiments that consider annotator expertise, example sel...
Jason Baldridge, Alexis Palmer
NN
2008
Springer
158views Neural Networks» more  NN 2008»
15 years 2 months ago
Improved mapping of information distribution across the cortical surface with the support vector machine
The early visual cortices represent information of several stimulus attributes, such as orientation and color. To understand the coding mechanisms of these attributes in the brain...
Youping Xiao, Ravi Rao, Guillermo A. Cecchi, Ehud ...
125
Voted
ICIP
2003
IEEE
16 years 3 months ago
Color photo categorization using compressed histograms and support vector machines
In this paper, an efficient method using various histogrambased (high-dimensional) image content descriptors for automatically classifying general color photos into relevant categ...
Xia Feng, Jianzhong Fang, Guoping Qiu