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» Support Vector Clustering for Brain Activation Detection
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ICPR
2010
IEEE
14 years 7 days ago
Exploiting Visual Quasi-Periodicity for Automated Chewing Event Detection Using Active Appearance Models and Support Vector Mach
We present a method that automatically detects chewing events in surveillance video of a subject. Firstly, an Active Appearance Model (AAM) is used to track a subject’s face acr...
Steven Cadavid, Mohamed Abdel-Mottaleb
VLDB
2007
ACM
164views Database» more  VLDB 2007»
14 years 5 months ago
A new intrusion detection system using support vector machines and hierarchical clustering
Whenever an intrusion occurs, the security and value of a computer system is compromised. Network-based attacks make it difficult for legitimate users to access various network ser...
Latifur Khan, Mamoun Awad, Bhavani M. Thuraisingha...
IJCNN
2007
IEEE
13 years 11 months ago
Neurolinguistic Approach to Vector Representation of Medical Concepts
Abstract—Putative brain processes responsible for understanding language are based on spreading activation in semantic networks, providing enhanced representations that involve c...
Wlodzislaw Duch, Pawel Matykiewicz, John Pestian
ISBI
2008
IEEE
14 years 6 months ago
Sensitivity analysis of parcellation in the joint detection-estimation of brain activity in fMRI
Within-subject analysis in fMRI relies on both (i) a detection step to localize which parts of the brain are activated by a given stimulus type, and on (ii) an estimation step to ...
Thomas Vincent, Philippe Ciuciu, Bertrand Thirion
MICCAI
2006
Springer
14 years 6 months ago
A Nonparametric Bayesian Approach to Detecting Spatial Activation Patterns in fMRI Data
Traditional techniques for statistical fMRI analysis are often based on thresholding of individual voxel values or averaging voxel values over a region of interest. In this paper w...
Hal S. Stern, Padhraic Smyth, Seyoung Kim