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    STUDIA INFORMATICA - Issue no. 4 / 2012  
         
  Article:   HOW THE KERNELS CAN INFLUENCE IMAGE CLASSIFICATION PERFORMANCE.

Authors:  LAURA DIOŞAN, ALEXANDRINA ROGOZAN.
 
       
         
  Abstract:  Support Vector Machines deliver state-of-the-art performance in real-world applications and are now established as one of the standard tools for machine learning and data mining. A key problem of these methods is how to choose an optimal kernel and how to optimise its parameters. Selection of the most appropriate kernel highly depends on the problem at hand and fine tuning its parameters can easily become a tiresome and awkward task. Our purpose is to investigate how the used kernels and their parameters influence the learning performance in the context of a particular classification task: object recognition. The numerical results indicate that the best kernel function depends on the problem to be solved.

Key words and phrases. Object recognition, Kernel descriptors, Support Vector Machines, Kernel selection.
 
         
     
         
         
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