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IPCV
2008
13 years 9 months ago
Neonatal Facial Pain Detection Using NNSOA and LSVM
- We report classification experiments using the pilot Infant COPE database of neonatal facial expressions. Two sets of DCT coeffiecents were used to train a neural network simulta...
Sheryl Brahnam, Loris Nanni, Randall S. Sexton
BMCBI
2007
178views more  BMCBI 2007»
13 years 7 months ago
SVM clustering
Background: Support Vector Machines (SVMs) provide a powerful method for classification (supervised learning). Use of SVMs for clustering (unsupervised learning) is now being cons...
Stephen Winters-Hilt, Sam Merat
ICB
2009
Springer
122views Biometrics» more  ICB 2009»
14 years 2 months ago
A New Fake Iris Detection Method
Recent research works have revealed that it is not difficult to spoof an automated iris recognition system using fake iris such as contact lens and paper print etc. Therefore, it i...
XiaoFu He, Yue Lu, Pengfei Shi
ICTAI
2006
IEEE
14 years 1 months ago
Modeling and Recognition of Gesture Signals in 2D Space: A Comparison of NN and SVM Approaches
In this paper we introduce a novel technique for modeling and recognizing gesture signals in 2D space. This technique is based on measuring the direction of the gradient of the mo...
Farhad Dadgostar, Abdolhossein Sarrafzadeh, Chao F...
ICML
2007
IEEE
14 years 8 months ago
Pegasos: Primal Estimated sub-GrAdient SOlver for SVM
We describe and analyze a simple and effective iterative algorithm for solving the optimization problem cast by Support Vector Machines (SVM). Our method alternates between stocha...
Shai Shalev-Shwartz, Yoram Singer, Nathan Srebro