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» Support Vector Machines for 3D Object Recognition
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96
Voted
CVPR
2004
IEEE
16 years 2 months ago
Cue Integration through Discriminative Accumulation
Object recognition systems aiming to work in real world settings should use multiple cues in order to achieve robustness. We present a new cue integration scheme which extends the...
Maria-Elena Nilsback, Barbara Caputo
106
Voted
CONEXT
2007
ACM
15 years 2 months ago
Detecting worm variants using machine learning
Network intrusion detection systems typically detect worms by examining packet or flow logs for known signatures. Not only does this approach mean worms cannot be detected until ...
Oliver Sharma, Mark Girolami, Joseph S. Sventek
108
Voted
ICML
2010
IEEE
15 years 1 months ago
COFFIN: A Computational Framework for Linear SVMs
In a variety of applications, kernel machines such as Support Vector Machines (SVMs) have been used with great success often delivering stateof-the-art results. Using the kernel t...
Sören Sonnenburg, Vojtech Franc
124
Voted
ICEIS
2010
IEEE
14 years 10 months ago
Pattern Recognition as a Human Centered non-Euclidean Problem
Regularities in the world are human defined. Patterns in the observed phenomena are there because we define and recognize them as such. Automatic pattern recognition tries to bridg...
Robert P. W. Duin
ICNC
2005
Springer
15 years 6 months ago
Multi-view Face Recognition with Min-Max Modular SVMs
Abstract. Through task decomposition and module combination, minmax modular support vector machines (M3 -SVMs) can be successfully used for difficult pattern classification task. ...
Zhi-Gang Fan, Bao-Liang Lu