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» Optimal feature selection for support vector machines
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ICIAR
2004
Springer
14 years 1 months ago
Real-Time Facial Feature Extraction by Cascaded Parameter Prediction and Image Optimization
We propose a new fast facial-feature extraction technique for embedded face-recognition applications. A deformable feature model is adopted, of which the parameters are optimized t...
Fei Zuo, Peter H. N. de With
ICIAR
2005
Springer
14 years 1 months ago
On the Individuality of the Iris Biometric
We consider quantitatively establishing the discriminative power of iris biometric data. It is difficult, however, to establish that any biometric modality is capable of distingui...
Sungsoo Yoon, Seung-Seok Choi, Sung-Hyuk Cha, Yill...
ICPR
2008
IEEE
14 years 2 months ago
RANSAC-SVM for large-scale datasets
Support Vector Machines (SVMs), though accurate, are still difficult to solve large-scale applications, due to the computational and storage requirement. To relieve this problem,...
Kenji Watanabe, Takio Kurita
ESANN
2008
13 years 9 months ago
Survival SVM: a practical scalable algorithm
This work advances the Support Vector Machine (SVM) based approach for predictive modelling of failure time data as proposed in [1]. The main results concern a drastic reduction in...
Vanya Van Belle, Kristiaan Pelckmans, Johan A. K. ...
MINENET
2006
ACM
14 years 1 months ago
SVM learning of IP address structure for latency prediction
We examine the ability to exploit the hierarchical structure of Internet addresses in order to endow network agents with predictive capabilities. Specifically, we consider Suppor...
Robert Beverly, Karen R. Sollins, Arthur Berger