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» Combining SVM Classifiers for Handwritten Digit Recognition
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ICPR
2004
IEEE
14 years 8 months ago
Two-Stage Classification System combining Model-Based and Discriminative Approaches
For the tasks of classification, two types of patterns can generate problems: ambiguous patterns and outliers. Furthermore, it is possible to separate classification algorithms in...
Jonathan Milgram, Mohamed Cheriet, Robert Sabourin
MVA
2007
133views Computer Vision» more  MVA 2007»
13 years 9 months ago
Selection of Object Recognition Methods According to the Task and Object Category
Service robots need object recognition strategy that can work on various objects in complex backgrounds. Since no single method can work in every situation, we need to combine sev...
Al Mansur, Yoshinori Kuno
CONEXT
2007
ACM
13 years 9 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
HCI
2009
13 years 5 months ago
Augmenting Sticky Notes as an I/O Interface
The design and implementation of systems that combine both the utilities of the digital world as well as intrinsic affordances of traditional artifacts are challenging. In this pap...
Pranav Mistry, Pattie Maes
PREMI
2007
Springer
14 years 1 months ago
Ensemble Approaches of Support Vector Machines for Multiclass Classification
Support vector machine (SVM) which was originally designed for binary classification has achieved superior performance in various classification problems. In order to extend it to ...
Jun-Ki Min, Jin-Hyuk Hong, Sung-Bae Cho