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ICASSP
2011
IEEE
12 years 8 months ago
Detecting human activities in retail surveillance using hierarchical finite state machine
Cashiers in retail stores usually exhibit certain repetitive and periodic activities when processing items. Detecting such activities plays a key role in most retail fraud detecti...
Hoang Trinh, Quanfu Fan, Jiyan Pan, Prasad Gabbur,...
AIME
1997
Springer
13 years 9 months ago
Detecting Very Early Stages of Dementia from Normal Aging with Machine Learning Methods
We used Machine Learning (ML) methods to learn the best decision rules to distinguish normal brain aging from the earliest stages of dementia using subsamples of 198 normal and 244...
William Rodman Shankle, Subramani Mani, Michael J....
MLMI
2007
Springer
13 years 11 months ago
Automatic Annotation of Dialogue Structure from Simple User Interaction
Abstract. In [1], we presented a method for automatic detection of action items from natural conversation. This method relies on supervised classification techniques that are trai...
Matthew Purver, John Niekrasz, Patrick Ehlen
AIME
2007
Springer
13 years 11 months ago
Machine Learning Techniques for Decision Support in Anesthesia
Abstract. The growing availability of measurement devices in the operating room enables the collection of a huge amount of data about the state of the patient and the doctors’ pr...
Olivier Caelen, Gianluca Bontempi, Luc Barvais
TMI
2010
172views more  TMI 2010»
13 years 3 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...